Details of the Researcher

PHOTO

Rin Tani
Section
Research Institute of Electrical Communication
Job title
Assistant Professor
Degree

  • PhD (the Australian National University)

Profile

Dr Lin Gu is working on the fundamental theory of artificial intelligence as well as its application on medical image analysis and computational photography.

For the medical image, his research covers multiple domains from MRI, CT to photoacoustic imaging. For computational photography, he is interested in enhancing the existing computer vision algorithm on extreme conditions such as low light, overexposure, low resolution, etc.

He joined RIKEN AIP in Tokyo in 2020 March as a research scientist. He is also a visiting scholar at the University of Tokyo, Japan. He was working at National Institute of Informatics (国立情報学研究所) in Tokyo from June 2016 to February 2020. From October 2016 to March 2019, He was also a regular visiting scholar at Kyoto University (京都大学). Before moving to Japan, he was a Postdoctoral Research Fellow at Bioinformatics Institute, A*STAR, Singapore. He completed his PhD studies at the Australian National University and NICTA (Now Data61) in 2014. At that time he was working on the hyperspectral imaging and colour science. After that, from 2014 to 2016, he was mainly focusing on the application of machine learning on biomedical imaging.

He has been awarded the MSRA Collaborative Research Grant in 2018 and JST ACT-X from 2019 to 2021

Research History 6

  • 2020/03 - 2025/11
    RIKEN　RIKEN Center for Advanced Intelligence Project (AIP)　Research Scientist

  • 2025/12 - Present
    Tohoku University　Research Institute of Electrical Communication　Assistant Professor

  • 2020/04 - 2025/11
    The University of Tokyo　Visiting Scholar

  • 2016/06 - 2020/02
    National Institute of Informatics　Project Researcher

  • 2016/06 - 2019/03
    Kyoto University　Visiting Scholar

  • 2014/03 - 2016/05
    A*STAR, Singapore　Postdoctoral Researcher Fellow

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Education 1

  • Australian National University　PhD

    2010/02 - 2014/12

Committee Memberships 17

  • Association for Computational Linguistics (ACL)　Area Chair

    2026/01 - Present

  • IEEE Transactions on Circuits and Systems for Video Technology　Associate Editor

    2025/11 - Present

  • Computer Vision and Pattern Recognition　Area Chair

    2025/09 - Present

  • Annual Conference on Neural Information Processing Systems (Neruips)　Area Chair

    2025/05 - Present

  • CVF/IEEE International Conference on Computer Vision (ICCV)　Area Chair

    2024/12 - Present

  • The Fourteenth International Conference on Learning Representations　Area Chair

    2024/09 - Present

  • International Conference on Machine Learning (ICML)　Area Chair

    2024/02 - Present

  • Medical Imaging Analysis: Current and Future Trends　Editor

    2024 - Present

  • Frontiers in Cardiovascular Medicine　Topic Editors

    2024 - Present

  • IET COMPUTER VISION　Guest Editor

    2023 - Present

  • Pattern Recognition　Associate Editor

    2023 - Present

  • IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)　Area Chair

    2025/06 - 2026/03

  • The 42st International Conference on Machine Learning (ICML'25)　Area Chair

    2024/11 - 2025/05

  • The 13th International Conference on Learning Representations (ICLR'25)　Area Chair

    2024/09 - 2025/05

  • The 39th Annual AAAI Conference on Artificial Intelligence (AAAI'25)　Senior Program Committee

    2024/08 - 2025/03

  • The 38th Annual Conference on Neural Information Processing Systems (NeurIPS'24)　Area Chair

    2024/05 - 2024/12

  • The 12th International Conference on Learning Representations　Area Chair

    2023/09 - 2024/05

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Research Interests 8

  • Neuroscience

  • Psychiatry

  • large language model

  • Photoacoustic Imaging

  • Computer Vision

  • Computational Photography

  • Medical Image Analysis

  • Artificial Intelligence

Research Areas 9

  • Life sciences / Evolutionary biology /

  • Informatics / Robotics and intelligent systems /

  • Energy / Nuclear fusion /

  • Life sciences / Psychiatry /

  • Life sciences / Cognitive neuroscience /

  • Informatics / Perceptual information processing / large language model

  • Life sciences / Neuroanatomy and physiology /

  • Life sciences / Medical systems /

  • Informatics / Intelligent informatics / Artificial Intellgience

Awards 4

  1. MSRA Collaborative Research 2018 Grant Awards

    2018/11　Microsoft Research Asia (MSRA)　Hololens Based Active Deep Learning for 3D Biomedical Imaging Analysis

  2. Best Student Paper Prize

    2013/12　Australian Pattern Recognition Society (APRS

  3. Best Student Paper Prize

    2012/12　International Pattern Recognition Society (IPRS)

  4. FB Rice Prize for the Best Patent Activity

    2012　NICTA

Papers 135

  1. Large language models for transportation energy integration: A functional framework and future directions Peer-reviewed

    Yongjian Chen, Shiqi Shawn Ou, Zhilong Lv, Zhifeng Yang, Lin Gu, Wei Ma

    Renewable and Sustainable Energy Reviews　241　117243-117243　2026/11

    Publisher: Elsevier BV

    DOI： 10.1016/j.rser.2026.117243 　

    ISSN： 1364-0321

  2. Stabilizing Hard-Negative Preference Optimization for Medical LLMs Peer-reviewed

    Kazuma Kobayashi, Yosuke Yamagishi, Ryota Shibaki, Azusa Sakai, Takashi Kodama, Lin Gu, Irene Li, Yuki Arase, Akiko Aizawa, Sadao Kurohashi

    Conference on Empirical Methods in Natural Language Processing (EMNLP 2026), Finding　2026/10

  3. A Physics-Guided Parametric Augmentation Net Peer-reviewed

    Chih-Ling Chang, Fu-Jen Tsai, Ziling Huang, Lin Gu, Chia-Wen Lin

    IEEE International Conference on Image Processing (ICIP)　2026/09

  4. Denoising the deep sky: physics-based CCD noise formation for astronomical imaging Peer-reviewed

    Shuhong Liu, Xining Ge, Ziying Gu, Quanfeng Xu, Lin Gu, Ziteng Cui, Xuangeng Chu, Jun Liu, Dong Li, Tatsuya Harada

    European Conference on Computer Vision (ECCV)　2026/09

  5. RealX3D: A Physically-Degraded 3D Benchmark for Multi-view Visual Restoration and Reconstruction Peer-reviewed

    Shuhong Liu, Chenyu Bao, Ziteng Cui, Yun Liu, Xuangeng Chu, Lin Gu, Marcos V. Conde, Ryo Umagami, Tomohiro Hashimoto, Zijian Hu, Tianhan Xu, Yuan Gan, Yusuke Kurose, Tatsuya Harada

    International Journal of Computer Vision　134　(8)　2026/08/03

    Publisher: Springer Science and Business Media LLC

    DOI： 10.1007/s11263-026-02963-4 　

    ISSN： 0920-5691

    eISSN： 1573-1405

    More details Close

    Abstract Reliable 3D reconstruction is a prerequisite for robotics, embodied AI, and immersive AR/VR applications; however, real-world observations frequently depart from clean imaging assumptions due to illumination changes, participating media, occlusions, and blur that break multi-view consistency and destabilize pose estimation, which leaves a gap between performance on curated benchmarks and behavior in practical deployments. To address this gap, we introduce RealX3D, a real capture benchmark for multi-view restoration and reconstruction under real-world degradations, organized into four families spanning nine controlled settings that include motion and defocus blur, low-light, view-varying exposure, smoke, dynamic occlusion, and reflection. RealX3D is collected using a unified acquisition protocol that enables recapturing the same camera trajectories to obtain pixel-aligned low-quality and reference ground-truth image pairs. Each scene also provides per-view RAW measurements to preserve high dynamic range linear sensor signals. To support geometry-grounded evaluation beyond image photometric fidelity, we capture dense laser scan geometry for every scene and derive world-scale measures such as point clouds, meshes, and metric depth, allowing comprehensive assessment of pose, depth, and surface reconstruction alongside photometric restoration quality. The benchmark contains 55 scenes recorded at high resolution with diverse real-world degradation patterns. We benchmark a broad set of optimization-based and feed-forward methods using both image metrics and geometry metrics, and the results reveal substantial robustness gaps across degradations in adverse conditions. Overall, RealX3D provides a rigorous benchmark that moves beyond synthetic data and establishes a standardized foundation for developing degradation-robust 3D reconstruction systems.

  6. Revisiting Photometric Ambiguity for Accurate Gaussian-Splatting Surface Reconstruction Peer-reviewed

    Jiahe Li, Jiawei Zhang, Xiao Bai, Jin Zheng, Xiaohan Yu, Lin Gu, Gim Hee Lee

    International Conference on Machine Learning (ICML)　2026/07

  7. ToolGrad: Efficient Tool-use Dataset Generation with Textual “Gradients” Peer-reviewed

    Zhongyi Zhou, Kohei Uehara, Haoyu Zhang, Jingtao Zhou, Lin Gu, Ruofei Du, Zheng Xu, Tatsuya Harada

    Annual Meeting of the Association for Computational Linguistics (ACL) Findings　2026/07

  8. REVEAL: Multimodal Vision–Language Alignment of Retinal Morphometry and Clinical Risks for Incident AD and Dementia Prediction Peer-reviewed

    Seowung Leem, Lin Gu, Chenyu You, Kuang Gong, Ruogu Fang

    Medical Imaging with Deep Learning　2026/07

  9. BETA: Resting-state fMRI Biotypes for tDCS Efficacy in Anxiety among Older Adults at Risk for Alzheimer's Disease Peer-reviewed

    Skylar Stolte, Junfu Cheng, Chintan Acharya, Lin Gu, Andrew O'Shea, Aprinda Indahlastari, Adam J. Woods, Ruogu Fang

    Medical Imaging with Deep Learning　2026/07

  10. Fourier Angle Alignment for Oriented Object Detection in Remote Sensing Peer-reviewed

    Changyu Gu, Linwei Chen, Lin Gu, Ying Fu

    Conference on Computer Vision and Pattern Recognition (CVPR)　2026/06

  11. SGI: Structured 2D Gaussians for Efficient and Compact Large Image Representation Peer-reviewed

    Zixuan Pan, Kaiyuan Tang, Jun Xia, Yifan Qin, Lin Gu, Chaoli Wang, Jianxu Chen, Yiyu Shi

    Conference on Computer Vision and Pattern Recognition (CVPR)　2026/06

  12. SMV-EAR: Bring Spatiotemporal Multi-View Representation Learning into Efficient Event-Based Action Recognition Peer-reviewed

    Rui Fan, Weidong Hao, Juntao Guan, Lai Rui, Tong Wu, Fanhong Zeng, Lin Gu

    Conference on Computer Vision and Pattern Recognition (CVPR)　2026/06

  13. NoisyEQA: benchmarking Embodied Question Answering with imperfect queries from non-expert users Peer-reviewed

    Tao Wu, Chuhao Zhou, Haozhi Cao, Yen Heng Wong, Lin Gu, Jianfei Yang

    Robot Learning　1-25　2026/05/19

    Publisher: ELS Publishing Co. Limited

    DOI： 10.55092/rl20260014 　

    ISSN： 2960-1436

    eISSN： 2960-1444

  14. Toward Efficient End-to-End VEM Processing Using a Unified Agent on GPUs and NPUs Peer-reviewed

    Haowen Xiao, Danyang Chen, Ziqian Guan, Xiangcheng Bao, Fangnan Xie, Jiarui Zhu, Jiayin Liang, Binqian Zou, Jiali Guana, Yanrui Lu, Chongyi Wang, Yuting Wang, Fukang Ge, Lin Gu, Jinhao Bic Jun He, Yingying Zhu

    International Symposium on Biomedical Imaging (ISBI)　2026/04

  15. Detection over Segmentation: A New Approach for Multi-Particle Picking in 3D Real-World CryoET Peer-reviewed

    Ziqian Guan, Yuting Wang, Danyang Chen, Jiarui Zhu, Haowen Xiao, FuKang Ge, Yanrui Lu, Lin Gu, Yingying Zhu

    International Symposium on Biomedical Imaging (ISBI)　2026/04

  16. Perception-Inspired Color Space Design for Photo White Balance Editing Peer-reviewed

    Yang Cheng, Ziteng Cui, Lin Gu, Shenghan Su, Zenghui Zhang

    Winter Conference on Applications of Computer Vision (WACV)　2026/03

  17. Aberrant fronto-limbic network in adolescents with attention-deficit/hyperactivity disorder: a multimodal MRI study using parallel ICA Peer-reviewed

    Jingqi He, Jinguang Li, Hongdi Pei, Ismael Benhouhou, Zhangyin He, Lin Gu, Jinsong Tang

    European Archives of Psychiatry and Clinical Neuroscience　2026/02/07

    Publisher: Springer Science and Business Media LLC

    DOI： 10.1007/s00406-026-02194-1 　

    ISSN： 0940-1334

    eISSN： 1433-8491

  18. DNGaussian++: Improving Sparse-View Gaussian Radiance Fields with Depth Normalization

    Jiahe Li, Jiawei Zhang, Xiaohan Yu, Xiao Bai, Jin Zheng, Xin Ning, Lin Gu

    IEEE Transactions on Pattern Analysis and Machine Intelligence　1-18　2026/01

    Publisher: Institute of Electrical and Electronics Engineers (IEEE)

    DOI： 10.1109/tpami.2026.3664307 　

    ISSN： 0162-8828

    eISSN： 2160-9292 1939-3539

  19. I2-NeRF: Learning Neural Radiance Fields Under Physically-Grounded Media Interactions Peer-reviewed

    Shuhong Liu, Lin Gu, Ziteng Cui, Xuangeng Chu, Tatsuya Harada

    Neural Information Processing Systems (Neruips 2025)　2025/12

  20. GeoSVR: Taming Sparse Voxels for Geometrically Accurate Surface Reconstruction Peer-reviewed

    Jiahe Li, Jiawei Zhang, Youmin Zhang, Xiao Bai, Jin Zheng, Xiaohan Yu, Lin Gu

    Neural Information Processing Systems (Neurips) 2025　2025/12

  21. Scene-aware contrastive regression for multi-person action quality assessment Peer-reviewed

    Xini Ding, Chunting Wang, Xuan Zhao, Huiliang Shang, Miao Wang, Lin Gu

    Applied Intelligence　55　(16)　2025/11/08

    Publisher: Springer Science and Business Media LLC

    DOI： 10.1007/s10489-025-06901-8 　

    ISSN： 0924-669X

    eISSN： 1573-7497

  22. Rehazing for Dehazing: A Physics-guided Parametric Augmentation Net Peer-reviewed

    Chih-Ling Chang, Fu-Jen Tsai, Ziling Huang, Lin Gu, Chia-Wen Lin

    IEEE Journal of Selected Topics in Signal Processing　1-14　2025/10

    Publisher: Institute of Electrical and Electronics Engineers (IEEE)

    DOI： 10.1109/jstsp.2025.3626262 　

    ISSN： 1932-4553

    eISSN： 1941-0484

  23. Frequency-Dynamic Attention Modulation For Dense Prediction Peer-reviewed

    Linwei Chen, Lin Gu, Ying Fu

    International Conference on Computer Vision (ICCV 2025)　2025/10

  24. Spatial Frequency Modulation for Semantic Segmentation Peer-reviewed

    Linwei Chen, Ying Fu, Lin Gu, Dezhi Zheng, Jifeng Dai

    IEEE Transactions on Pattern Analysis and Machine Intelligence　1-18　2025/07

    Publisher: Institute of Electrical and Electronics Engineers (IEEE)

    DOI： 10.1109/tpami.2025.3592621 　

    ISSN： 0162-8828

    eISSN： 2160-9292 1939-3539

  25. Investigating Synthetic-to-Real Transfer Robustness for Stereo Matching and Optical Flow Estimation Peer-reviewed

    Jiawei Zhang, Jiahe Li, Lei Huang, Haonan Luo, Xiaohan Yu, Lin Gu, Jin Zheng, Xiao Bai

    IEEE Transactions on Pattern Analysis and Machine Intelligence　1-18　2025/07

    Publisher: Institute of Electrical and Electronics Engineers (IEEE)

    DOI： 10.1109/tpami.2025.3584847 　

    ISSN： 0162-8828

    eISSN： 2160-9292 1939-3539

  26. Frequency Dynamic Convolution for Dense Image Prediction International-journal International-coauthorship Peer-reviewed

    Linwei Chen, Lin Gu, Liang Li, Chenggang Yan, Ying Fu

    Conference on Computer Vision and Pattern Recognition (CVPR)　abs/2503.18783　2025/06

    DOI： 10.48550/arXiv.2503.18783 　

  27. InsTaG: Learning Personalized 3D Talking Head from Few-Second Video International-journal International-coauthorship Peer-reviewed

    Jiahe Li, Jiawei Zhang, Xiao Bai, Jin Zheng, Jun Zhou, Lin Gu

    Conference on Computer Vision and Pattern Recognition (CVPR)　abs/2502.20387　2025/06

    DOI： 10.48550/arXiv.2502.20387 　

  28. Coronary Artery Segmentation with Partial Annotations in Coronary CT Angiography Images Peer-reviewed

    Yusuke Kurose, Haruto Chiba, Lin Gu, Junichi Iho, Youji Tokunaga, Makoto Horie, Keisuke Nishizawa, Yusaku Hayashi, Yasushi Koyama, Tatsuya Harada

    2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI)　1-5　2025/04/14

    Publisher: IEEE

    DOI： 10.1109/isbi60581.2025.10980766 　

  29. Physiology-Aware PolySnake for Coronary Vessel Segmentation Peer-reviewed

    Yizhe Ruan, Lin Gu, Yusuke Kurose, Junichi Iho, Youji Tokunaga, Makoto Horie, Yusaku Hayashi, Keisuke Nishizawa, Yasushi Koyama, Tatsuya Harada

    2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)　8873-8882　2025/02/26

    Publisher: IEEE

    DOI： 10.1109/wacv61041.2025.00860 　

  30. EventPillars: Pillar-based Efficient Representations for Event Data Peer-reviewed

    Rui Fan, Weidong Hao, Juntao Guan, Lai Rui, Lin Gu, Tong Wu, Fanhong Zeng, Zhangming Zhu

    Annual AAAI Conference on Artificial Intelligence (AAAI)　2025/02

  31. Semantic-guided Masked Mutual Learning for Multi-modal Brain Tumor Segmentation with Arbitrary Missing Modalities Peer-reviewed

    Guoyan Liang, Qin Zhou, Zhe Wang, Jingyuan Chen, Lin Gu, Chang Yao, Sai Wu, Bingcang Huang, Kai Chen

    Annual AAAI Conference on Artificial Intelligence (AAAI)　2025/02

  32. TdAttenMix: Top-Down Attention Guided Mixup International-journal International-coauthorship Peer-reviewed

    Zhiming Wang, Lin Gu, Feng Lu

    Annual AAAI Conference on Artificial Intelligence (AAAI)　2025/02

  33. Emergence of Painting Ability via Recognition-Driven Evolution.

    Yi Lin, Lin Gu 0003, Ziteng Cui, Shenghan Su, Yumo Hao, Yingtao Tian, Tatsuya Harada, Jianfei Yang

    CoRR　abs/2501.04966　2025/01

    DOI： 10.48550/arXiv.2501.04966 　

  34. Evaluating the Effectiveness of advanced large language models in medical Knowledge: A Comparative study using Japanese national medical examination Peer-reviewed

    Mingxin Liu, Tsuyoshi Okuhara, Zhehao Dai, Wenbo Huang, Lin Gu, Hiroko Okada, Emi Furukawa, Takahiro Kiuchi

    International Journal of Medical Informatics　193　105673-105673　2025/01

    Publisher: Elsevier BV

    DOI： 10.1016/j.ijmedinf.2024.105673 　

    ISSN： 1386-5056

  35. Frequency-Aware Feature Fusion for Dense Image Prediction.

    Linwei Chen, Ying Fu 0001, Lin Gu 0003, Chenggang Yan 0001, Tatsuya Harada, Gao Huang 0001

    IEEE Transactions on Pattern Analysis and Machine Intelligence　46　(12)　10763-10780　2024/12

    DOI： 10.1109/TPAMI.2024.3449959 　

  36. TinyLUT: Tiny Look-Up Table for Efficient Image Restoration at the Edge Peer-reviewed

    Huanan Li, Juntao Guan, Rui Lai, Sijun Ma, Lin Gu, Zhangming Zhu

    Annual Conference on Neural Information Processing Systems (Neruips 2024)　2024/11

  37. Defender of privacy and fairness: Tiny but reversible generative model via mutually collaborative knowledge distillation Peer-reviewed

    Sissi Xiaoxiao Wu, Zehong Huang, Zhicong Liang, Lin Gu, Tatsuya Harada, Zheng Li, Yingying Zhu

    Neurocomputing　128822-128822　2024/11

    Publisher: Elsevier BV

    DOI： 10.1016/j.neucom.2024.128822 　

    ISSN： 0925-2312

  38. Advancing Mental Health Care: Intelligent Assessments and Automated Generation of Personalized Advice via M.I.N.I and RoBERTa Peer-reviewed

    Yuezhong Wu, Huan Xie, Lin Gu, Rongrong Chen, Shanshan Chen, Fanglan Wang, Yiwen Liu, Lingjiao Chen, Jinsong Tang

    Applied Sciences　14　(20)　9447-9447　2024/10/16

    Publisher: MDPI AG

    DOI： 10.3390/app14209447 　

    eISSN： 2076-3417

    More details Close

    As mental health issues become increasingly prominent, we are now facing challenges such as the severe unequal distribution of medical resources and low diagnostic efficiency. This paper integrates finite state machines, retrieval algorithms, semantic-matching models, and medical-knowledge graphs to design an innovative intelligent auxiliary evaluation tool and a personalized medical-advice generation application, aiming to improve the efficiency of mental health assessments and the provision of personalized medical advice. The main contributions include the folowing: (1) Developing an auxiliary diagnostic tool that combines the Mini-International Neuropsychiatric Interview (M.I.N.I.) with finite state machines to systematically collect patient information for preliminary assessments; (2) Enhancing data processing by optimizing retrieval algorithms for efficient filtering and employing a fine-tuned RoBERTa model for deep semantic matching and analysis, ensuring accurate and personalized medical-advice generation; (3) Generating intelligent suggestions using NLP techniques; when semantic matching falls below a specific threshold, integrating medical-knowledge graphs to produce general medical advice. Experimental results show that this application achieves a semantic-matching degree of 0.9 and an accuracy of 0.87, significantly improving assessment accuracy and the ability to generate personalized medical advice. This optimizes the allocation of medical resources, enhances diagnostic efficiency, and provides a reference for advancing mental health care through artificial-intelligence technology.

  39. Discovering an Image-Adaptive Coordinate System for Photography Processing Peer-reviewed

    Ziteng Cui, Lin Gu, Tatsuya Harada

    British Machine Vision Conference (BMVC 2024)　abs/2501.06448　2024/10

    DOI： 10.48550/arXiv.2501.06448 　

  40. Object-Aware NIR-to-Visible Translation International-journal International-coauthorship Peer-reviewed

    Yunyi Gao, Lin Gu, Qiankun Liu, Ying Fu

    European Conference on Computer Vision (ECCV 2024)　2024/10

  41. TalkingGaussian: Structure-Persistent 3D Talking Head Synthesis via Gaussian Splatting International-journal International-coauthorship Peer-reviewed

    Jiahe Li, Jiawei Zhang, Xiao Bai, Jin Zheng, Xin Ning, Jun Zhou, Lin Gu

    European Conference on Computer Vision (ECCV 2024)　2024/10

  42. CoR-GS: Sparse-View 3D Gaussian Splatting via Co-Regularization International-journal International-coauthorship Peer-reviewed

    Jiawei Zhang, Jiahe Li, Xiaohan Yu, Lei Huang, Lin Gu, Jin Zheng, Xiao Bai

    European Conference on Computer Vision (ECCV 2024)　2024/10

  43. ER-NeRF++: Efficient region-aware Neural Radiance Fields for high-fidelity talking portrait synthesis Peer-reviewed

    Jiahe Li, Jiawei Zhang, Xiao Bai, Jin Zheng, Jun Zhou, Lin Gu

    Information Fusion　110　102456-102456　2024/10

    Publisher: Elsevier BV

    DOI： 10.1016/j.inffus.2024.102456 　

    ISSN： 1566-2535

  44. Circadian Rhythms Correlated in DNA Methylation and Gene Expression Identified in Human Blood and Implicated in Psychiatric Disorders Peer-reviewed

    Haiyan Tang, Shanshan Chen, Liu Yi, Sheng Xu, Huihui Yang, Zongchang Li, Ying He, Yanhui Liao, Xiaogang Chen, Chunyu Liu, Lin Gu, Ning Yuan, Chao Chen, Jinsong Tang

    American Journal of Medical Genetics Part B: Neuropsychiatric Genetics　2024/09/25

    Publisher: Wiley

    DOI： 10.1002/ajmg.b.33005 　

    ISSN： 1552-4841

    eISSN： 1552-485X

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    ABSTRACT Circadian rhythms modulate the biology of many human tissues and are driven by a nearly 24‐h transcriptional feedback loop. Dynamic DNA methylation may play a role in driving 24‐h rhythms of gene expression in the human brain. However, little is known about the degree of circadian regulation between the DNA methylation and the gene expression in the peripheral tissues, including human blood. We hypothesized that 24‐h rhythms of DNA methylation play a role in driving 24‐h RNA expression in human blood. To test this hypothesis, we analyzed DNA methylation levels and RNA expression in blood samples collected from eight healthy males at six‐time points over 24 h. We assessed 442,703 genome‐wide CpG sites in methylation and 12,364 genes in expression for 24‐h rhythmicity using the cosine model. Our analysis revealed significant rhythmic patterns in 6345 CpG sites and 21 genes. Next, we investigated the relationship between methylation and expression using powerful circadian signals. We found a modest negative correlation (ρ = −0.83, p = 0.06) between the expression of gene TXNDC5 and the methylation at the nearby CpG site (cg19116172). We also observed that circadian CpGs significantly overlapped with genetic risk loci of schizophrenia and autism spectrum disorders. Notably, one gene, TXNDC5, showed a significant correlation between circadian methylation and expression and has been reported to be association with neuropsychiatric diseases.

  45. Learning From Human Attention for Attribute-Assisted Visual Recognition Peer-reviewed

    Xiao Bai, Pengcheng Zhang, Xiaohan Yu, Jin Zheng, Edwin R. Hancock, Jun Zhou, Lin Gu

    IEEE Transactions on Pattern Analysis and Machine Intelligence　1-16　2024/09

    Publisher: Institute of Electrical and Electronics Engineers (IEEE)

    DOI： 10.1109/tpami.2024.3458921 　

    ISSN： 0162-8828

    eISSN： 2160-9292 1939-3539

  46. A New Benchmark: Clinical Uncertainty and Severity Aware Labeled Chest X-Ray Images with Multi-Relationship Graph Learning Peer-reviewed

    Mengliang Zhang, Xinyue Hu, Lin Gu, Liangchen Liu, Kazuma Kobayashi, Tatsuya Harada, Yan Yan, Ronald M. Summers, Yingying Zhu

    IEEE Transactions on Medical Imaging　1-1　2024/08

    Publisher: Institute of Electrical and Electronics Engineers (IEEE)

    DOI： 10.1109/tmi.2024.3441494 　

    ISSN： 0278-0062

    eISSN： 1558-254X

  47. Rethinking masked image modeling for medical image representation

    Yutong Xie, Lin Gu, Tatsuya Harada, Jianpeng Zhang, Yong Xia, Qi Wu

    Medical Image Analysis　103304-103304　2024/08

    Publisher: Elsevier BV

    DOI： 10.1016/j.media.2024.103304 　

    ISSN： 1361-8415

  48. Interpretable medical image visual question answering via multi-modal relationship graph learning Peer-reviewed

    Xinyue Hu, Lin Gu, Kazuma Kobayashi, Liangchen Liu, Mengliang Zhang, Tatsuya Harada, Ronald Summers, Yingying Zhu

    Medical Image Analysis　103279-103279　2024/07

    Publisher: Elsevier BV

    DOI： 10.1016/j.media.2024.103279 　

    ISSN： 1361-8415

  49. Using convolutional neural networks to detect edge localized modes in DIII-D from Doppler backscattering measurements

    N. Q. X. Teo, V. H. Hall-Chen, K. Barada, R. J. H. Ng, L. Gu, A. K. Yeoh, Q. T. Pratt, X. Garbet, T. L. Rhodes

    Review of Scientific Instruments　95　(7)　2024/07/01

    Publisher: AIP Publishing

    DOI： 10.1063/5.0215748 　

    ISSN： 0034-6748

    eISSN： 1089-7623

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    In H-mode tokamak plasmas, the plasma is sometimes ejected beyond the edge transport barrier. These events are known as edge localized modes (ELMs). ELMs cause a loss of energy and damage the vessel walls. Understanding the physics of ELMs, and by extension, how to detect and mitigate them, is an important challenge. In this paper, we focus on two diagnostic methods—deuterium-alpha (Dα) spectroscopy and Doppler backscattering (DBS). The former detects ELMs by measuring Balmer alpha emission, while the latter uses microwave radiation to probe the plasma. DBS has the advantages of having a higher temporal resolution and robustness to damage. These advantages of DBS diagnostic may be beneficial for future operational tokamaks, and thus, data processing techniques for DBS should be developed in preparation. In sight of this, we explore the training of neural networks to detect ELMs from DBS data, using Dα data as the ground truth. With shots found in the DIII-D database, the model is trained to classify each time step based on the occurrence of an ELM event. The results are promising. When tested on shots similar to those used for training, the model is capable of consistently achieving a high f1-score of 0.93. This score is a performance metric for imbalanced datasets that ranges between 0 and 1. We evaluate the performance of our neural network on a variety of ELMs in different high confinement regimes (grassy ELM, RMP mitigated, and wide-pedestal), finding broad applicability. Beyond ELMs, our work demonstrates the wider feasibility of applying neural networks to data from DBS diagnostic.

  50. Can physician judgment enhance model trustworthiness? A case study on predicting pathological lymph nodes in rectal cancer

    Kazuma Kobayashi, Yasuyuki Takamizawa, Mototaka Miyake, Sono Ito, Lin Gu, Tatsuya Nakatsuka, Yu Akagi, Tatsuya Harada, Yukihide Kanemitsu, Ryuji Hamamoto

    Artificial Intelligence in Medicine　102929-102929　2024/07

    Publisher: Elsevier BV

    DOI： 10.1016/j.artmed.2024.102929 　

    ISSN： 0933-3657

  51. Content-Specific Humorous Image Captioning Using Incongruity Resolution Chain-of-Thought Peer-reviewed

    Kohtaro Tanaka, Kohei Uehara, Lin Gu, Yusuke Mukuta, Tatsuya Harada

    Findings of the Association for Computational Linguistics (NAACL Findings)　2024/06

  52. DNGaussian: Optimizing Sparse-View 3D Gaussian Radiance Fields with Global-Local Depth Normalization International-journal International-coauthorship

    Jiahe Li, Jiawei Zhang, Xiao Bai, Jin Zheng, Xin Ning, Jun Zhou, Lin Gu

    Computer Vision and Pattern Recognition Conference (CVPR)　2024/06

  53. Adaptive Dilated Convolution from Frequency View International-journal International-coauthorship Peer-reviewed

    Linwei Chen, Lin Gu, Dezhi Zheng, Ying Fu

    Computer Vision and Pattern Recognition Conference (CVPR)　2024/06

  54. Robust Synthetic-to-Real Transfer for Stereo Matching International-journal International-coauthorship Peer-reviewed

    Jiawei Zhang, Jiahe Li, Lei Huang, Xiaohan Yu, Lin Gu, Jin Zheng, Xiao Bai

    Computer Vision and Pattern Recognition Conference (CVPR)　2024/06

  55. Exploring the Usage of Pre-trained Features for Stereo Matching International-journal International-coauthorship Peer-reviewed

    Jiawei Zhang, Lei Huang, Xiao Bai, Jin Zheng, Lin Gu, Edwin Hancock

    International Journal of Computer Vision　2024/05/11

    Publisher: Springer Science and Business Media LLC

    DOI： 10.1007/s11263-024-02090-y 　

    ISSN： 0920-5691

    eISSN： 1573-1405

  56. When Semantic Segmentation Meets Frequency Aliasing International-journal International-coauthorship Peer-reviewed

    Linwei Chen, Lin Gu, Ying Fu

    The International Conference on Learning Representations (ICLR)　2024/05

  57. Multiple serum anti-glutamate receptor antibody levels in clozapine-treated/naïve patients with treatment-resistant schizophrenia Peer-reviewed

    Jingqi He, Jinguang Li, Yisen Wei, Zhangyin He, Junyu Liu, Ning Yuan, Risheng Zhou, Xingtao He, Honghong Ren, Lin Gu, Yanhui Liao, Xiaogang Chen, Jinsong Tang

    BMC Psychiatry　24　(1)　2024/04/02

    Publisher: Springer Science and Business Media LLC

    DOI： 10.1186/s12888-024-05689-0 　

    eISSN： 1471-244X

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    Abstract Background Glutamatergic function abnormalities have been implicated in the etiology of treatment-resistant schizophrenia (TRS), and the efficacy of clozapine may be attributed to its impact on the glutamate system. Recently, evidence has emerged suggesting the involvement of immune processes and increased prevalence of antineuronal antibodies in TRS. This current study aimed to investigate the levels of multiple anti-glutamate receptor antibodies in TRS and explore the effects of clozapine on these antibody levels. Methods Enzyme linked immunosorbent assay (ELISA) was used to measure and compare the levels of anti-glutamate receptor antibodies (NMDAR, AMPAR, mGlur3, mGluR5) in clozapine-treated TRS patients (TRS-C, n = 37), clozapine-naïve TRS patients (TRS-NC, n = 39), and non-TRS patients (nTRS, n = 35). Clinical symptom severity was assessed using the Positive and Negative Symptom Scale (PANSS), while cognitive function was evaluated using the MATRICS Consensus Cognitive Battery (MCCB). Result The levels of all four glutamate receptor antibodies in TRS-NC were significantly higher than those in nTRS (p < 0.001) and in TRS-C (p < 0.001), and the antibody levels in TRS-C were comparable to those in nTRS. However, no significant associations were observed between antibody levels and symptom severity or cognitive function across all three groups after FDR correction. Conclusion Our findings suggest that TRS may related to increased anti-glutamate receptor antibody levels and provide further evidence that glutamatergic dysfunction and immune processes may contribute to the pathogenesis of TRS. The impact of clozapine on anti-glutamate receptor antibody levels may be a pharmacological mechanism underlying its therapeutic effects.

  58. Aleth-NeRF: Illumination Adaptive NeRF with Concealing Field Assumption Peer-reviewed

    Ziteng Cui, Lin Gu, Xiao Sun, Xianzheng Ma, Yu Qiao, Tatsuya Harada

    AAAI Conference on Artificial Intelligence (AAAI)　2024/02

  59. Discovering an Image-Adaptive Coordinate System for Photography Processing.

    Ziteng Cui, Lin Gu 0003, Tatsuya Harada

    BMVC　2024

  60. Frequency-Adaptive Dilated Convolution for Semantic Segmentation.

    Linwei Chen, Lin Gu 0003, Dezhi Zheng, Ying Fu 0001

    IEEE/CVF Conference on Computer Vision and Pattern Recognition(CVPR)　3414-3425　2024

    Publisher: IEEE

    DOI： 10.1109/CVPR52733.2024.00328 　

  61. Sketch-based semantic retrieval of medical images Peer-reviewed

    Kazuma Kobayashi, Lin Gu, Ryuichiro Hataya, Takaaki Mizuno, Mototaka Miyake, Hirokazu Watanabe, Masamichi Takahashi, Yasuyuki Takamizawa, Yukihiro Yoshida, Satoshi Nakamura, Nobuji Kouno, Amina Bolatkan, Yusuke Kurose, Tatsuya Harada, Ryuji Hamamoto

    Medical Image Analysis　103060-103060　2023/12

    Publisher: Elsevier BV

    DOI： 10.1016/j.media.2023.103060 　

    ISSN： 1361-8415

  62. MedIM: Boost Medical Image Representation via Radiology Report-guided Masking Peer-reviewed

    Yutong Xie, Lin Gu, Tatsuya Harada, Jianpeng Zhang, Yong Xia, Qi Wu

    Medical Image Computing and Computer-Assisted Intervention 2023　2023/10

  63. Efficient Region-Aware Neural Radiance Fields for High-Fidelity Talking Portrait Synthesis Peer-reviewed

    Jiahe Li, Jiawei Zhang, Xiao Bai, Jun Zhou, Lin Gu

    International Conference on Computer Vision 2023　2023/10

  64. Name Your Colour For the Task: Artificially Discover Colour Naming via Colour Quantisation Transformer Peer-reviewed

    Shenghan Su, Lin Gu, Yue Yang, Zenghui Zhang, Tatsuya Harada

    International Conference on Computer Vision (ICCV) 2023　2023/10

  65. Towards AI-driven radiology education: A self-supervised segmentation-based framework for high-precision medical image editing Peer-reviewed

    Kazuma Kobayashi, Lin Gu, Ryuichiro Hataya, Mototaka Miyake, Yasuyuki Takamizawa, Sono Ito, Hirokazu Watanabe, Yukihiro Yoshida, Hiroki Yoshimura, Tatsuya Harada, yuji Hamamoto

    Medical Image Computing and Computer-Assisted Intervention (MICCAI 2023)　2023/10

  66. Correlated and individual feature learning with contrast-enhanced MR for malignancy characterization of hepatocellular carcinoma Peer-reviewed

    Yunling Li, Shangxuan Li, Hanqiu Ju, Tatsuya Harada, Honglai Zhang, Ting Duan, Guangyi Wang, Lijuan Zhang, Lin Gu, Wu Zhou

    Pattern Recognition　142　109638-109638　2023/10

    Publisher: Elsevier BV

    DOI： 10.1016/j.patcog.2023.109638 　

    ISSN： 0031-3203

  67. PATCH : A Plug-in Framework of Non-blocking Inference for Distributed Multimodal System Peer-reviewed

    Juexing Wang, Guangjing Wang, Xiao Zhang, Li Liu, Huacheng Zeng, Li Xiao, Zhichao Cao, Lin Gu, Tianxing Li

    Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies　7　(3)　1-24　2023/09/27

    Publisher: Association for Computing Machinery (ACM)

    DOI： 10.1145/3610885 　

    eISSN： 2474-9567

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    Recent advancements in deep learning have shown that multimodal inference can be particularly useful in tasks like autonomous driving, human health, and production line monitoring. However, deploying state-of-the-art multimodal models in distributed IoT systems poses unique challenges since the sensor data from low-cost edge devices can get corrupted, lost, or delayed before reaching the cloud. These problems are magnified in the presence of asymmetric data generation rates from different sensor modalities, wireless network dynamics, or unpredictable sensor behavior, leading to either increased latency or degradation in inference accuracy, which could affect the normal operation of the system with severe consequences like human injury or car accident. In this paper, we propose PATCH, a framework of speculative inference to adapt to these complex scenarios. PATCH serves as a plug-in module in the existing multimodal models, and it enables speculative inference of these off-the-shelf deep learning models. PATCH consists of 1) a Masked-AutoEncoder-based cross-modality imputation module to impute missing data using partially-available sensor data, 2) a lightweight feature pair ranking module that effectively limits the searching space for the optimal imputation configuration with low computation overhead, and 3) a data alignment module that aligns multimodal heterogeneous data streams without using accurate timestamp or external synchronization mechanisms. We implement PATCH in nine popular multimodal models using five public datasets and one self-collected dataset. The experimental results show that PATCH achieves up to 13% mean accuracy improvement over the state-of-art method while only using 10% of training data and reducing the training overhead by 73% compared to the original cost of retraining the model.

  68. Expert Knowledge-Aware Image Difference Graph Representation Learning for Difference-Aware Medical Visual Question Answering Peer-reviewed

    Xinyue Hu, Lin Gu, Qiyuan An, Zhang Mengliang, Liangchen Liu, Kazuma Kobayashi, Tatsuya Harada, Ronald, M. Summers, Yingying Zhu

    SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023)　2023/08

  69. Sex differences in the association of treatment-resistant schizophrenia and serum interleukin-6 levels Peer-reviewed

    Jingqi He, Yisen Wei, Jinguang Li, Ying Tang, Junyu Liu, Zhangyin He, Risheng Zhou, Xingtao He, Honghong Ren, Yanhui Liao, Lin Gu, Ning Yuan, Xiaogang Chen, Jinsong Tang

    BMC Psychiatry　23　(1)　2023/06/27

    Publisher: Springer Science and Business Media LLC

    DOI： 10.1186/s12888-023-04952-0 　

    eISSN： 1471-244X

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    Abstract Background Low-grade inflammation and altered inflammatory markers have been observed in treatment-resistant schizophrenia (TRS). Interleukin-6 (IL-6) is one of the pro-inflammatory cytokines linked with TRS and receives increasing attention. Previous studies showed that patients with TRS might have higher IL-6 levels compared with healthy individuals and treatment-responsive patients. Besides, emerging evidence has suggested that there are sex differences in the associations between IL-6 levels and various illnesses, including chronic hepatitis C, metabolic syndrome, etc.; however, there is limited study on TRS. In this present study, we aimed to compare the serum IL-6 levels of TRS and partially responsive schizophrenia (PRS) and explore potential sex differences in the association of TRS and IL-6 levels. Methods The study population consisted of a total of 90 patients with schizophrenia: 64 TRS patients (45.3% males and 54.7% females) and 26 PRS patients (46.2% males and 53.8% females). We measured serum IL-6 levels using enzyme-linked immunosorbent assay (ELISA) and analyzed them separately by gender, controlling for confounders (age, education, medication, body mass index, and PANSS scores) rigorously. Result The results showed that patients with TRS had higher serum IL-6 levels than patients with PRS (p = 0.002). In females, IL-6 levels increased significantly in the TRS group compared with the PRS group (p = 0.005). And a positive correlation tendency was observed between IL-6 levels and PANSS general sub-scores (r = 0.31, p = 0.039), although this correlation was not significant after correcting for multiple comparisons. Whereas, there were no differences in IL-6 levels between the TRS and PRS (p = 0.124) in males. Conclusion Our findings provided evidence supporting the hypothesis that the inflammatory response system (IRS) may play a role in the pathogenesis of TRS in a sex-dependent manner. In addition, sex differences in the immune dysfunction of individuals with schizophrenia cannot be neglected, and inflammation in male and female TRS should be discussed separately.

  70. 3D Segmenter: 3D Transformer based Semantic Segmentation via 2D Panoramic Distillation Peer-reviewed

    ZHENNAN WU, YANG LI, Yifei Huang, Lin Gu, Tatsuya Harada, Hiroyuki Sato

    International Conference on Learning Representations　2023/05

  71. BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets Invited

    Linus Manubens-Gil, Zhi Zhou, Hanbo Chen, Arvind Ramanathan, Xiaoxiao Liu, Yufeng Liu, Alessandro Bria, Todd Gillette, Zongcai Ruan, Jian Yang, Miroslav Radojević, Ting Zhao, Li Cheng, Lei Qu, Siqi Liu, Kristofer E. Bouchard, Lin Gu, Weidong Cai, Shuiwang Ji, Badrinath Roysam, Ching-Wei Wang, Hongchuan Yu, Amos Sironi, Daniel Maxim Iascone, Jie Zhou, Erhan Bas, Eduardo Conde-Sousa, Paulo Aguiar, Xiang Li, Yujie Li, Sumit Nanda, Yuan Wang, Leila Muresan, Pascal Fua, Bing Ye, Hai-yan He, Jochen F. Staiger, Manuel Peter, Daniel N. Cox, Michel Simonneau, Marcel Oberlaender, Gregory Jefferis, Kei Ito, Paloma Gonzalez-Bellido, Jinhyun Kim, Edwin Rubel, Hollis T. Cline, Hongkui Zeng, Aljoscha Nern, Ann-Shyn Chiang, Jianhua Yao, Jane Roskams, Rick Livesey, Janine Stevens, Tianming Liu, Chinh Dang, Yike Guo, Ning Zhong, Georgia Tourassi, Sean Hill, Michael Hawrylycz, Christof Koch, Erik Meijering, Giorgio A. Ascoli, Hanchuan Peng

    Nature Methods　2023/04/17

    Publisher: Springer Science and Business Media LLC

    DOI： 10.1038/s41592-023-01848-5 　

    ISSN： 1548-7091

    eISSN： 1548-7105

  72. Differences in olfactory dysfunction and its relationship with cognitive function in schizophrenia patients with and without auditory verbal hallucinations Peer-reviewed

    Qianjin Wang, Honghong Ren, Zongchang Li, Jinguang Li, Lulin Dai, Min Dong, Jun Zhou, Jingqi He, Xiaogang Chen, Lin Gu, Ying He, Jinsong Tang

    European Archives of Psychiatry and Clinical Neuroscience　2023/03/22

    Publisher: Springer Science and Business Media LLC

    DOI： 10.1007/s00406-023-01589-8 　

    ISSN： 0940-1334

    eISSN： 1433-8491

  73. The COVID-19 pandemic in various restriction policy scenarios based on the dynamic social contact rate Peer-reviewed

    Hui Hu, Shuaizhou Xiong, Xiaoling Zhang, Shuzhou Liu, Lin Gu, Yuqi Zhu, Dongjin Xiang, Martin Skitmore

    Heliyon　9　(3)　e14533-e14533　2023/03

    Publisher: Elsevier BV

    DOI： 10.1016/j.heliyon.2023.e14533 　

    ISSN： 2405-8440

  74. People taking photos that faces never share: Privacy Protection and Fairness Enhancement from Camera to User Peer-reviewed

    Junjie Zhu, Lin Gu, Xiaoxiao Wu, zheng li, Tatsuya Harada, Yingying Zhu

    AAAI Conference on Artificial Intelligence　2023/02

  75. Sketch-based Medical Image Retrieval.

    Kazuma Kobayashi, Lin Gu 0003, Ryuichiro Hataya, Takaaki Mizuno, Mototaka Miyake, Hirokazu Watanabe, Masamichi Takahashi, Yasuyuki Takamizawa, Yukihiro Yoshida, Satoshi Nakamura, Nobuji Kouno, Amina Bolatkan, Yusuke Kurose, Tatsuya Harada, Ryuji Hamamoto

    CoRR　abs/2303.03633　2023

    DOI： 10.48550/arXiv.2303.03633 　

  76. Readmission Prediction for Heart Failure Patients Using Features Extracted From SS-MIX Peer-reviewed

    Hiroaki Yamane, Yusuke Kurose, Antonio Tejero-de-Pablos, Lin Gu, Junichi Iho, Youji Tokunaga, Makoto Horie, Yusaku Hayashi, Keisuke Nishizawa, Yasushi Koyama, Tatsuya Harada

    2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&ISIS)　2022/11/29

    Publisher: IEEE

    DOI： 10.1109/scisisis55246.2022.10001907 　

  77. Improving Fairness in Image Classification via Sketching Peer-reviewed

    Ruichen Yao, Ziteng Cui, Xiaoxiao Li, Lin Gu

    NeurIPS 2022, Workshop on Trustworthy and Socially Responsible Machine Learning　2022/11

  78. You Only Need 90K Parameters to Adapt Light: a Light Weight Transformer for Image Enhancement and Exposure Correction Peer-reviewed

    Ziteng Cui, Kunchang Li, Lin Gu, Shenghan Su, Peng Gao, ZhengKai Jiang, Yu Qiao, Tatsuya Harada

    The British Machine Vision Conference　2022/11

  79. Where to Focus: Investigating Hierarchical Attention Relationship for Fine-Grained Visual Classification Peer-reviewed

    Yang Liu, Lei Zhou, Pengcheng Zhang, Xiao Bai, Lin Gu, Xiaohan Yu, Jun Zhou, Hancock Edwin

    European Conference on Computer Vision 2022　2022/10

    DOI： 10.1007/978-3-031-20053-3_4 　

  80. Exploring Resolution and Degradation Clues as Self-supervised Signal for Low Quality Object Detection Peer-reviewed

    Ziteng Cui, Yingying Zhu, Lin Gu, Guo-Jun Qi, Xiaoxiao Li, Renrui Zhang, Zenghui Zhang, Tatsuya Harada

    European Conference on Computer Vision 2022　2022/10

  81. Information bottleneck and selective noise supervision for zero-shot learning

    Lei Zhou, Yang Liu, Pengcheng Zhang, Xiao Bai, Lin Gu, Jun Zhou, Yazhou Yao, Tatsuya Harada, Jin Zheng, Edwin Hancock

    Machine Learning　2022/09/01

    Publisher: Springer Science and Business Media LLC

    DOI： 10.1007/s10994-022-06196-7 　

    ISSN： 0885-6125

    eISSN： 1573-0565

  82. Surgical Skill Assessment via Video Semantic Aggregation Peer-reviewed

    Zhenqiang Li, Lin Gu, Weimin Wang, Ryosuke Nakamura, Yoichi Sato

    International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI)　2022/09

  83. Memory-Efficient Deformable Convolution based Joint Denoising and Demosaicing for UHD Images

    Juntao Guan, Rui Lai, Yang Lu, Yangang Li, Huanan Li, Lichen Feng, Yintang Yang, Lin Gu

    IEEE Transactions on Circuits and Systems for Video Technology　1-1　2022/06

    Publisher: Institute of Electrical and Electronics Engineers (IEEE)

    DOI： 10.1109/tcsvt.2022.3182990 　

    ISSN： 1051-8215

    eISSN： 1558-2205

  84. Revisiting Domain Generalized Stereo Matching Networks from a Feature Consistency Perspective Peer-reviewed

    Jiawei Zhang, Xiang Wang, Xiao Bai, Chen Wang, Lei Huang, Yimin Chen, Lin Gu, Jun Zhou, Tatsuya Harada, Edwin R. Hancock

    Conference on Computer Vision and Pattern Recognition (CVPR) 2022　2022/06

  85. Deficits in Sense of Body Ownership, Sensory Processing, and Temporal Perception in Schizophrenia Patients With/Without Auditory Verbal Hallucinations Peer-reviewed

    Jingqi He, Honghong Ren, Jinguang Li, Min Dong, Lulin Dai, Zhijun Li, Yating Miao, Yunjin Li, Peixuan Tan, Lin Gu, Xiaogang Chen, Jinsong Tang

    Frontiers in Neuroscience　16　2022/04/14

    Publisher: Frontiers Media SA

    DOI： 10.3389/fnins.2022.831714 　

    eISSN： 1662-453X

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    It has been claimed that individuals with schizophrenia have difficulty in self-recognition and, consequently, are unable to identify the sources of their sensory perceptions or thoughts, resulting in delusions, hallucinations, and unusual experiences of body ownership. The deficits also contribute to the enhanced rubber hand illusion (RHI; a body perception illusion, induced by synchronous visual and tactile stimulation). Evidence based on RHI paradigms is emerging that auditory information can make an impact on the sense of body ownership, which relies on the process of multisensory inputs and integration. Hence, we assumed that auditory verbal hallucinations (AVHs), as an abnormal auditory perception, could be linked with body ownership, and the RHI paradigm could be conducted in patients with AVHs to explore the underlying mechanisms. In this study, we investigated the performance of patients with/without AVHs in the RHI. We administered the RHI paradigm to 80 patients with schizophrenia (47 with AVHs and 33 without AVHs) and 36 healthy controls. We conducted the experiment under two conditions (synchronous and asynchronous) and evaluated the RHI effects by both objective and subjective measures. Both patient groups experienced the RHI more quickly and strongly than HCs. The RHI effects of patients with AVHs were significantly smaller than those of patients without AVHs. Another important finding was that patients with AVHs did not show a reduction in RHI under asynchronous conditions. These results emphasize the disturbances of the sense of body ownership in schizophrenia patients with/without AVHs and the associations with AVHs. Furthermore, it is suggested that patients with AVHs may have multisensory processing dysfunctions and internal timing deficits.

  86. Graph interaction for automated diagnosis of thoracic disease using x-ray images Peer-reviewed

    Bumjun Jung, Lin Gu, Tatsuya Harada

    Medical Imaging 2022: Image Processing　2022/04/04

    Publisher: SPIE

    DOI： 10.1117/12.2612707 　

  87. Visual detection and tracking algorithms for minimally invasive surgical instruments: A comprehensive review of the state-of-the-art Peer-reviewed

    Yan Wang, Qiyuan Sun, Zhenzhong Liu, Lin Gu

    Robotics and Autonomous Systems　149　103945-103945　2022/03

    Publisher: Elsevier BV

    DOI： 10.1016/j.robot.2021.103945 　

    ISSN： 0921-8890

  88. DnRCNN: Deep Recurrent Convolutional Neural Network for HSI Destriping Peer-reviewed

    Juntao Guan, Rui Lai, Huanan Li, Yintang Yang, Lin Gu

    IEEE Transactions on Neural Networks and Learning Systems　1-14　2022/02

    Publisher: Institute of Electrical and Electronics Engineers (IEEE)

    DOI： 10.1109/tnnls.2022.3142425 　

    ISSN： 2162-237X

    eISSN： 2162-2388

  89. EtinyNet: Extremely Tiny Network for TinyML Peer-reviewed

    Kunran Xu, Yishi Li, Huawei Zhang, Rui Lai, Lin Gu

    AAAI Conference on Artificial Intelligence (AAAI)　2022/02

  90. Towards an Effective Orthogonal Dictionary Convolution Strategy Peer-reviewed

    Yishi Li, Kunran Xu, Rui Lai, Lin Gu

    AAAI Conference on Artificial Intelligence (AAAI)　2022/02

  91. A Study of Fractional Amplitude of Low Frequency Fluctuation in Schizophrenia Patients with Persistent Verbal Auditory Hallucinations Peer-reviewed

    Qianjin Wang, Honghong Ren, Zongchang Li, Jinguang Li, Lulin Dai, Min Dong, Jun Zhou, Jingqi He, Ying He, Lin Gu, Xiaogang Chen, Jinsong Tang

    Journal of Psychiatry and Brain Science　7　(6)　2022

    Publisher: Hapres

    DOI： 10.20900/jpbs.20220014 　

    eISSN： 2398-385X

  92. The etiology of auditory hallucinations in schizophrenia: from multidimensional levels Peer-reviewed

    Xu Shao, Yanhui Liao, Lin Gu, Wei Chen, Jinsong Tang

    Frontiers in Neuroscience, section Brain Imaging Methods　2021/12

  93. Leveraging Human Selective Attention for Medical Image Analysis with Limited Training Data Peer-reviewed

    Yifei Huang, Xiaoxiao Li, Lijin Yang, Lin Gu, Yingying Zhu, Hirofumi Seo, Qiuming Meng, Tatsuya Harada, Yoichi Sato

    The British Machine Vision Conference (BMVC)　2021/12

  94. Multitask AET with Orthogonal Tangent Regularity for Dark Object Detection Peer-reviewed

    Ziteng Cui, Guo-Jun Qi, Lin Gu, Shaodi You, Zenghui Zhang, Tatsuya Harada

    International Conference on Computer Vision (ICCV 2021)　2021/11

  95. Goal-oriented gaze estimation for zero-shot learning Peer-reviewed

    Yang Liu, Lei Zhou, Xiao Bai, Yifei Huang, Lin Gu, Jun Zhou, Tatsuya Harada

    Conference on Computer Vision and Pattern Recognition (CVPR 2021)　abs/2103.03433　2021/06

  96. Multiresolution Discriminative Mixup Network for Fine-Grained Visual Categorization Peer-reviewed

    Kunran Xu, Rui Lai, Lin Gu, Yishi Li

    IEEE Transactions on Neural Networks and Learning Systems　1-13　2021

    Publisher: Institute of Electrical and Electronics Engineers (IEEE)

    DOI： 10.1109/tnnls.2021.3112768 　

    ISSN： 2162-237X

    eISSN： 2162-2388

  97. Explainable Diabetic Retinopathy Detection and Retinal Image Generation Peer-reviewed

    Yuhao Niu, Lin Gu, Yitian Zhao, Feng Lu

    IEEE Journal of Biomedical and Health Informatics　1-1　2021

    Publisher: Institute of Electrical and Electronics Engineers (IEEE)

    DOI： 10.1109/jbhi.2021.3110593 　

    ISSN： 2168-2194

    eISSN： 2168-2208

  98. An Improved ICP Algorithm for Point Cloud Registration Peer-reviewed

    Guodong Sun, Yan Wang, Lin Gu, Zhenzhong Liu

    IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)　2021

  99. Object Detection of Surgical Instruments Based on YOLOv4 Peer-reviewed

    Yan Wang, qiyuan Sun, Guodong Sun, Lin Gu, Zhenzhong Liu

    IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)　2021

  100. Relation-Aware Reasoning with Graph Convolutional Network Peer-reviewed

    Lei Zhou, Yang Liu, Xiao Bai, Xiang Wang, Chen Wang, Liang Zhang, Lin Gu

    International Conference on Image and Graphics (ICIG)　2021

  101. Beyond Triplet Loss: Person Re-identification with Fine-grained Difference-aware Pairwise Loss Peer-reviewed

    Cheng Yan, Guansong Pang, Xiao Bai, Changhong Liu, Ning Xin, Lin Gu, Jun Zhou

    IEEE Transactions on Multimedia　1-1　2021

    Publisher: Institute of Electrical and Electronics Engineers (IEEE)

    DOI： 10.1109/tmm.2021.3069562 　

    ISSN： 1520-9210

    eISSN： 1941-0077

  102. Review of Deep Learning Approaches for the Segmentation of Multiple Sclerosis Lesions on Brain MRI Peer-reviewed

    Chenyi Zeng, Lin Gu, Zhenzhong Liu, Shen Zhao

    Frontiers in Neuroinformatics　14　2020/11/20

    Publisher: Frontiers Media SA

    DOI： 10.3389/fninf.2020.610967 　

    eISSN： 1662-5196

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    In recent years, there have been multiple works of literature reviewing methods for automatically segmenting multiple sclerosis (MS) lesions. However, there is no literature systematically and individually review deep learning-based MS lesion segmentation methods. Although the previous review also included methods based on deep learning, there are some methods based on deep learning that they did not review. In addition, their review of deep learning methods did not go deep into the specific categories of Convolutional Neural Network (CNN). They only reviewed these methods in a generalized form, such as supervision strategy, input data handling strategy, etc. This paper presents a systematic review of the literature in automated multiple sclerosis lesion segmentation based on deep learning. Algorithms based on deep learning reviewed are classified into two categories through their CNN style, and their strengths and weaknesses will also be given through our investigation and analysis. We give a quantitative comparison of the methods reviewed through two metrics: Dice Similarity Coefficient (DSC) and Positive Predictive Value (PPV). Finally, the future direction of the application of deep learning in MS lesion segmentation will be discussed.

  103. Semi-Supervised Learning in Medical Images Through Graph-Embedded Random Forest Peer-reviewed

    Lin Gu, Xiaowei Zhang, Shaodi You, Shen Zhao, Zhenzhong Liu, Tatsuya Harada

    Frontiers in Neuroinformatics　14　2020/11/10

    Publisher: Frontiers Media SA

    DOI： 10.3389/fninf.2020.601829 　

    eISSN： 1662-5196

  104. Feature Normalized Knowledge Distillation for Image Classification Peer-reviewed

    Kunran Xu, Lai Rui, Yishi Li, Lin Gu

    European Conference on Computer Vision (ECCV 2020)　2020/08

  105. Motion Feedback Design for Video Frame Interpolation Peer-reviewed

    Mengshun Hu, Liang Liao, Jing Xiao, Lin Gu, Shin’ichi Satoh

    IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)　4347-4351　2020/05

    Publisher: IEEE

    DOI： 10.1109/ICASSP40776.2020.9053223 　

  106. Understanding adversarial attacks on deep learning based medical image analysis systems Peer-reviewed

    Xingjun Ma, Yuhao Niu, Lin Gu, Yisen Wang, Yitian Zhao, James Bailey, Feng Lu

    Pattern Recognition　2020/05

  107. City-Scale Distance Sensing via Bispectral Light Extinction in Bad Weather Peer-reviewed

    Dong Zhao, Yuta Asano, Lin Gu, Imari Sato, Huixin Zhou

    Remote Sensing　12　(9)　1401-1401　2020/04/29

    Publisher: MDPI AG

    DOI： 10.3390/rs12091401 　

    eISSN： 2072-4292

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    In this paper, we propose a novel city-scale distance sensing algorithm based on atmosphere optics. The suspended particles, especially in bad weather, would attenuate the light at almost all wavelengths. Observing this fact and starting from the light scattering mechanism, we derive a bispectral distance sensing algorithm by leveraging the difference of extinction coefficient between two specifically selected near infrared wavelengths. The extinction coefficient of the atmosphere is related to both wavelength and meteorological conditions, also known as visibility, such as the fog and haze day. To account for different bad weather conditions, we explicitly introduce visibility into our algorithm by incorporating it into the calculation of extinction coefficient, making our algorithm simple yet effective. To capture the data, we build a bispectral imaging system that is able to take a pair of images with a monochrome camera and two narrow band-pass filters. We also present a wavelength selection strategy that allows us to accurately sense distance regardless of material reflectance and texture. Specifically, this strategy determines two distinct near infrared wavelengths by maximising the extinction coefficient difference while minimizing the influence of building’s reflectance variance. The experiments empirically validate our model and its practical performance on the distance sensing for the city-scale buildings.

  108. Advancing Image Understanding in Poor Visibility Environments: A Collective Benchmark Study Peer-reviewed

    Wenhan Yang, Ye Yuan, Wenqi Ren, Jiaying Liu, Walter J Scheirer, Zhangyang Wang, Taiheng Zhang, Qiaoyong Zhong, Di Xie, Shiliang Pu, Yuqiang Zheng, Yanyun Qu, Yuhong Xie, Liang Chen, Zhonghao Li, Chen Hong, Hao Jiang, Siyuan Yang, Yan Liu, Xiaochao Qu, Pengfei Wan, Shuai Zheng, Minhui Zhong, Taiyi Su, Lingzhi He, Yandong Guo, Yao Zhao, Zhenfeng Zhu, Jinxiu Liang, Jingwen Wang, Tianyi Chen, Yuhui Quan, Yong Xu, Bo Liu, Xin Liu, Qi Sun, Tingyu Lin, Xiaochuan Li, Feng Lu, Lin Gu, Shengdi Zhou, Cong Cao, Shifeng Zhang, Cheng Chi, Chubing Zhuang, Zhen Lei, Stan Z Li, Shizheng Wang, Ruizhe Liu, Dong Yi, Zheming Zuo, Jianning Chi, Huan Wang, Kai Wang, Yixiu Liu, Xingyu Gao, Zhenyu Chen, Chang Guo, Yongzhou Li, Huicai Zhong, Jing Huang, Heng Guo, Jianfei Yang, Wenjuan Liao, Jiangang Yang, Liguo Zhou, Mingyue Feng, Likun Qin

    IEEE Transactions on Image Processing　29　5737-5752　2020/03

  109. Target tracking from infrared imagery via an improved appearance model Peer-reviewed

    D Zhao, L Gu, K Qian, H Zhou, T Yang, K Cheng

    Infrared Physics & Technology　2020/01

  110. RGB-IR Cross Input and Sub-Pixel Upsampling Network for Infrared Image Super-Resolution Peer-reviewed

    J Du, H Zhou, K Qian, W Tan, Z Zhang, L Gu, Y Yu

    Sensors　2020/01

  111. Hyperspectral Anomaly Detection via Tensor-Based Endmember Extraction and Low-Rank Decomposition Peer-reviewed

    S Song, H Zhou, L Gu, Y Yang, Y Yang

    IEEE Geoscience and Remote Sensing Letters　2019/12

  112. ShelfNet for Fast Semantic Segmentation Peer-reviewed

    J Zhuang, J Yang, L Gu, N Dvornek

    IEEE International Conference on Computer Vision Workshops　2019/11

  113. Single-Image Facial Expression Recognition Using Deep 3D Re-Centralization Peer-reviewed

    Z Bao, S You, L Gu, Z Yang

    Proceedings of the IEEE International Conference on Computer Vision Workshops　2019/11

  114. Unsupervised Ensemble Strategy for Retinal Vessel Segmentation Peer-reviewed

    B Liu, L Gu, F Lu

    International Conference on Medical Image Computing and Computer-Assisted Intervention　2019/11

  115. Fixed pattern noise reduction for infrared images based on cascade residual attention CNN Peer-reviewed

    J Guan, R Lai, A Xiong, Z Liu, L Gu

    Neurocomputing　2019/11

  116. Discrepancy Steered Conditional Adversarial Network for Deep Feature Based Malignancy Characterization of Hepatocellular Carcinoma

    Hanqiu Ju, Guangyi Wang, Shaoyang Men, Honglai Zhang, Lin Gu, Wu Zhou

    Proceedings - International Conference on Image Processing, ICIP　2019-　1342-1345　2019/09/01

    Publisher: IEEE Computer Society

    DOI： 10.1109/ICIP.2019.8804297 　

    ISSN： 1522-4880

  117. Improving the malignancy characterization of hepatocellular carcinoma using deeply supervised cross modal transfer learning for non-enhanced MR

    Wanwei Jian, Hanqiu Ju, Xiaoping Cen, Manman Cui, Honglai Zhang, Lijuan Zhang, Guangyi Wang, Lin Gu, Wu Zhou

    Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS　853-856　2019/07/01

    Publisher: Institute of Electrical and Electronics Engineers Inc.

    DOI： 10.1109/EMBC.2019.8857467 　

    ISSN： 1557-170X

  118. Automated leg tracking reveals distinct conserved gait and tremor signatures in Drosophila models of Parkinson's Disease and Spinocerebellar ataxia 3 Peer-reviewed

    Sherry Shiying Aw, Shuang Wu, Kah Junn Tan, Lakshmi Narasimhan Govindarajan, James Charles Stewart, Lin Gu, Joses Wei Hao Ho, Malvika Katarya, Boon Hui Wong, Eng-King Tan, Daiqin Li, Adam Claridge-Chang, Camio David Libedinsky, Li Cheng

    PLOS Biology　2019/06

  119. Machine learning-based structural analysis and oxygen saturation measurement of tumor-associated vessels in breast cancer using a photoacoustic tomography system Peer-reviewed

    Y Matsumoto, L Gu, R Bise, Y Asao, H Sekiguchi, A Yoshikawa, T Ishii, M Takada, M Kataoka, T Sakurai, T Yagi, I Sato, K Togashi, T Shiina, M Toi

    Cancer Research　2019/02

  120. Pathological evidence exploration in deep retinal image diagnosis Peer-reviewed

    Y Niu, L Gu, F Lu, F Lv, Z Wang, I Sato, Z Zhang, Y Xiao, X Dai, T Cheng

    AAAI conference on artificial intelligence　1093-1101　2019/02

    Publisher: AAAI Press

    DOI： 10.1609/aaai.v33i01.33011093 　

  121. Hyperspectral Anomaly Detection with Harmonic Analysis and Low-Rank Decomposition Peer-reviewed

    P Xiang, J Song, H Li, L Gu, H Zhou

    Remote Sensing　2019/01

  122. Deeply Learned Filter Response Functions for Hyperspectral Reconstruction

    Shijie Nie, Lin Gu, Yinqiang Zheng, Antony Lam, Nobutaka Ono, Imari Sato

    2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition　2018/06

    Publisher: IEEE

    DOI： 10.1109/cvpr.2018.00501 　

  123. A Data-Driven Approach for Direct and Global Component Separation from a Single Image. Peer-reviewed

    Shijie Nie, Lin Gu 0003, Art Subpa-Asa, Ilyes Kacher, Ko Nishino, Imari Sato

    Asian Conference on Computer Vision　133-148　2018

    Publisher: Springer

    DOI： 10.1007/978-3-030-20876-9_9 　

  124. From RGB to Spectrum for Natural Scenes via Manifold-Based Mapping

    Yan Jia, Yinqiang Zheng, Lin Gu, Art Subpa-Asa, Antony Lam, Yoichi Sato, Imari Sato

    2017 IEEE International Conference on Computer Vision (ICCV)　2017/10

    Publisher: IEEE

    DOI： 10.1109/iccv.2017.504 　

  125. Semi-supervised Learning for Biomedical Image Segmentation via Forest Oriented Super Pixels(Voxels)

    Lin Gu, Yinqiang Zheng, Ryoma Bise, Imari Sato, Nobuaki Imanishi, Sadakazu Aiso

    Medical Image Computing and Computer Assisted Intervention − MICCAI 2017　702-710　2017/09/04

    Publisher: Springer International Publishing

    DOI： 10.1007/978-3-319-66182-7_80 　

    ISSN： 0302-9743

    eISSN： 1611-3349

  126. Virtual Blood Vessels in Complex Background Using Stereo X-Ray Images Peer-reviewed

    Q Chen, R Bise, L Gu, Y Zheng, I Sato, JN Hwang, N Imanishi, S Aiso

    IEEE International Conference on Computer Vision Workshops　2017/06

  127. Segment 2D and 3D Filaments by Learning Structured and Contextual Features Peer-reviewed

    Lin Gu, Xiaowei Zhang, He Zhao, Huiqi Li, Li Cheng

    IEEE TRANSACTIONS ON MEDICAL IMAGING　36　(2)　596-606　2017/02

    DOI： 10.1109/TMI.2016.2623357 　

    ISSN： 0278-0062

    eISSN： 1558-254X

  128. Classification from a Riemannian Graph Embedding Viewpoint Peer-reviewed

    Antonio Robles-Kelly, Lin Gu, Ran Wei

    2016 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN)　3288-3295　2016

    ISSN： 2161-4393

  129. A QUADRATIC OPTIMISATION APPROACH FOR SHADING AND SPECULARITY RECOVERY FROM A SINGLE IMAGE Peer-reviewed

    Lin Gu, Antonio Robles-Kelly

    2016 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP)　4072-4076　2016

    ISSN： 1522-4880

  130. Learning to Boost Filamentary Structure Segmentation Peer-reviewed

    Lin Gu, Li Cheng

    2015 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV)　639-647　2015

    DOI： 10.1109/ICCV.2015.80 　

    ISSN： 1550-5499

  131. Segmentation and Estimation of Spatially Varying Illumination Peer-reviewed

    Lin Gu, Cong Phuoc Huynh, Antonio Robles-Kelly

    IEEE TRANSACTIONS ON IMAGE PROCESSING　23　(8)　3478-3489　2014/08

    DOI： 10.1109/TIP.2014.2330768 　

    ISSN： 1057-7149

    eISSN： 1941-0042

  132. Shadow modelling based upon Rayleigh scattering and Mie theory Peer-reviewed

    Lin Gu, Antonio Robles-Kelly

    PATTERN RECOGNITION LETTERS　43　89-97　2014/07

    DOI： 10.1016/j.patrec.2013.10.020 　

    ISSN： 0167-8655

    eISSN： 1872-7344

  133. Reconstructing Polarisation Components from Unpolarised Images Peer-reviewed

    Lin Gu, Cong Phuoc Huynh, Antonio Robles-Kelly

    2013 INTERNATIONAL CONFERENCE ON DIGITAL IMAGE COMPUTING: TECHNIQUES & APPLICATIONS (DICTA)　80-87　2013

  134. Shadow Detection via Rayleigh Scattering and Mie Theory Peer-reviewed

    Lin Gu, Antonio Robles-Kelly

    2012 21ST INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR 2012)　2165-2168　2012

    ISSN： 1051-4651

  135. Material-Specific User Colour Profiles from Imaging Spectroscopy Data Peer-reviewed

    Lin Gu, Cong Phuoc Huynh, Antonio Robles-Kelly, Jun Zhou

    2011 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV)　1987-1994　2011

    ISSN： 1550-5499

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Books and Other Publications 3

  1. Cybernetic Avatar

    Hiroshi Ishiguro, Fuki Ueno, Eiki Tachibana

    Springer Singapore　2024/10

    ISBN: 9789819737543

  2. Artificial Intelligence in Clinical Medicine

    Lin Gu

    2023/03

  3. Handbook of pattern recognition and computer vision

    World Scientific　2016

    ISBN: 9789814656528

Presentations 13

  1. Towards Evolutionary Foundation Models Beyond Human Supervision Invited

    Lin Gu

    Exploring Foundation Models in Medical Image Analysis: Applications, Challenges, and Uncertainties　2026/04/10

  2. From explainability to engagment: Human-Centric Transparent and Privacy-Aware AI Invited

    Lin Gu

    Second ICCV workshop on Fairness and ethics towards transparent AI: facing the chalLEnge through model Debiasing (FAILED)　2025/10/20

  3. How Human Evolve Story Telling ability, evidence from neuronscience and art Invited

    Lin Gu

    ICCV 2025 Workshop on Generative AI for Storytelling (AISTORY)　2025/10/20

  4. Bridging the Gap in Medical AI research Invited

    Lin Gu

    CVPR Medical Computer Vision Workshop　2025/06/12

  5. Computer Vision & AI for Health Invited

    Lin Gu, Alexandra Wolf, Evan Shelhamer, Yalda Mohsenzadeh

    2nd Vector Institute ＆ RIKEN AIP Joint Symposium on Machine Learning and Artificial Intelligence　2025/03/25

  6. Artificial Cortex from Evolution Invited

    Lin Gu

    Vector Institute ＆ RIKEN AIP Joint Symposium on Machine Learning and Artificial Intelligence　2025/03/25

  7. Artificial Cortex from Evolution Invited

    Lin Gu

    UW - RIKEN AIP Joint Workshop　2025/03/21

  8. Artificial Cortex from Evolution: Synthesizing Multimodal Intelligence for Next-Generation AI Invited

    Lin Gu

    Case Western Spring Colloquium　2025/03/06

  9. Evolutionary Pathways: From Physical Signals to High-Level Cognition in AI Invited

    Lin Gu

    IIT: Istituto Italiano di Tecnologia　2024/09/26

  10. Recognition in a physical world: an evolutionary approach Invited

    Lin Gu

    The 2nd RIKEN AIP – SJTU CS Joint Workshop on Machine Learning and Brain-like Intelligence　2024/08/06

  11. Exploring Medical Know-how Knowledge under Evolutionary Approach Invited

    Lin Gu

    The 6th Annual Meeting of the Japanese Association for Medical Artificial Intelligence　2024/06/22

  12. Representation learning from physical world to cognition

    Lin Gu

    RIKEN-IIT Joint Workshop　2024/05/20

  13. Beyond RGB: Transfer Image Knowledge to Multimodal Learning Invited

    Lin Gu

    NVIDIA GTC 2021　2021/04/13

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Industrial Property Rights 3

  1. Optimised colour response function for material classification

    Lin Gu, Shijie Nie, Yinqiang Zheng, Imari Sato

    Property Type: Patent

  2. Image clustering for estimation of illumination spectra

    Lin Gu, Cong Huynh, Antonio Robles-Kelly

    Property Type: Patent

  3. Determining colour values in hyperspectral or multispectral images

    Lin Gu, Cong P. Huynh, Antonio Robles-Kelly

    Property Type: Patent

Research Projects 6

  1. Continous Learning and Memory Mechanism

    Lin Gu

    Offer Organization: JST

    System: ムーンショット型研究開発事業（ムーンショット目標1）「2050年までに、人が身体、脳、空間、時間の制約から解放された社会を実現」

    Category: artificial intelligence

    Institution: RIKEN

    2020/01 - 2025/10

  2. Subtyping schizophrenia using artificial intelligence approach

    Lin Gu, Tang Jingsong

    Offer Organization: RIKEN MOST

    System: MOST-RIKEN

    Category: artificial intelligence

    Institution: RIKEN

    2022/07 - 2025/06

  3. Interpretable Deep Learning Framework that Generates Pixel-wise Labels from Human Interaction acceleration phase

    Lin Gu

    Offer Organization: JST

    System: ACT-X acceleration phase

    Category: Interpretable Deep Learning Framework that Generates Pixel-wise Labels from Human Interaction

    Institution: RIKEN

    2022/03 - 2023/03

  4. Interpretable Deep Learning Framework that Generates Pixel-wise Labels from Human Interaction Competitive

    Lin Gu

    Offer Organization: JST

    System: ACT-X

    Category: artificial intelligence

    Institution: RIKEN

    2019/10 - 2021/03

  5. Hololens Based Active Deep Learning for 3D Biomedical Imaging Analysis Competitive

    Lin Gu, Imari Sato

    Offer Organization: Microsoft Research Asia (MSRA)

    System: Collaborative Research

    Category: artificial intelligence

    Institution: NII

    2018/01 - 2018/12

  6. Single-shot Hyperspectral Fluorescent Imaging

    ZHENG YINQIANG, SATO Imari, MEGURO Misaki, ASANO Yuta, JIA Yan, GU Lin, SATO Yoichi

    Offer Organization: Japan Society for the Promotion of Science

    System: Grants-in-Aid for Scientific Research

    Category: Grant-in-Aid for Young Scientists (B)

    Institution: National Institute of Informatics

    2016/04 - 2018/03

    More details Close

    There are many objects and substances around us, like dyes and plants, which contain both the reflective and fluorescent components. To separate the reflective component from the fluorescent component is helpful in examining the intrinsic status of objects. Therefore, effective methods for this separation task are needed. Existing methods for fluorescence and reflectance separation needs multiple shots under different illuminations, thus are inapplicable to dynamic scenes. This research first uses a single hyperspectral image, and designs the optimal illumination spectrum for this separation task. The fact that existing hyperspectral cameras are still not very fast in data capture leads us to explore the possibility of reconstructing hyperspectral images from RGB images. On the application aspect, a simple separation method of weak fluorescence in the presence of strong environmental illumination has been developed and successfully used for freshness examination of meat and cheese.

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Teaching Experience 2

  1. Special Topics in Mechano-InformaticsII　The University of Tokyo

  2. Special Lecture on Pattern Recognition　Tohoku University

Media Coverage 2

  1. スケッチで画像検索が可能なAIシステムを開発：希少疾患なども効率的な検索が可能に

    がん情報サイト「オンコロ」　https://oncolo.jp/news/240105ra01

    2024/01

    Type: Internet

  2. 国がん、膨大なCT・MRIの画像をスケッチにより検索するAIを開発

    TECH+　https://news.mynavi.jp/techplus/article/20231225-2850204/

    Type: Internet

Academic Activities 3

  1. Neural Information Processing Systems

    2024/12 - 2024/12

    Activity type: Academic society, research group, etc.

  2. International Conference on Machine Learning

    2024/07 - 2024/07

    Activity type: Academic society, research group, etc.

  3. The International Conference on Learning Representations (ICLR)

    2023/05 - 2023/05

    Activity type: Academic society, research group, etc.