个人简介
梁毅雄，男，中南大学计算机学院教授，入选“湖南省普通高校青年骨干教师培养对象”，中南大学531计划第三层次人才。一直从事于计算机视觉与机器学习、数字图像/医学影像处理等方面的研究，主持国家自然科学基金项目、国家重点研发计划子课题任务、湖南省自然科学基金、教育部博士点基金等多项国家及省部级科研课题，获授权发明专利20余项；在ICCV、NeurIPS、ACM MM、MICCAI等国际顶级会议和PR, IEEE JBHI, IEEE/ACM TCBB, IEEE TCSVT, and ACM TIST等权威期刊上发表论文70余篇。担任CVPR、ICLR、NeurIPS、ICML、AAAI、ACM MM、MICCAI等国际顶级会议程序委员会委员/审稿人，以及IEEE TIP、IEEE TMI、IEEE TC、IEEE JBHI、自动化学报、电子学报等国内外权威期刊的审稿人。
2009年被评为“湖南省普通高校青年骨干教师培养对象”；2011年7月至2012年7月在美国卡耐基梅隆大学机器人研究所（Robotics Institute, Carnegie Mellon University）进行访问研究。
目前主要研究兴趣包括基于多模态学习的目标检测、图像语义/实例分割、计算机辅助筛查与诊断、智能机器人等方面的研究与应用，承担《机器学习》、《计算机视觉》、《深度学习技术》、《数字图像处理》等本科生课程和《数字图像处理及应用》等研究生课程的教学工作。
欢迎对多模态学习、计算机视觉、智慧医疗与智能机器人等方面具有浓厚兴趣的优秀同学加入！ (Email: yxliang[at]csu[dot]edu[dot]cn; QQ：6532695; Mobile/WeChat: 13548670948 )
近期论文列表(Google Scholar, DBLP)
[1] Bolei Chen, Jiaxu Kang, Ping Zhong, Yixiong Liang, Yu Sheng, and Jianxin Wang, “Embodied Contrastive Learning with Geometric Consistency and Behavioral Awareness for Object Navigation,” in ACM international conference on Multimedia (ACM MM), 2024. (Accept)
[2] Lina Huang, Yixiong Liang, and Jianfeng Liu, “DES-SAM: Distillation-Enhanced Semantic SAM for Cervical Nuclear Segmentation with Box Annotation,” in International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2024. (Accept)
[3] Ziyuan Ding, Yixiong Liang, Shichao Kan, and Qing Liu, “HRDecoder: High-Resolution Decoder Network for Fundus Image Lesion Segmentation,” in International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2024. (Early Accept)
[4] Shu Wang, Zhe Qu, Yuan Liu, Shichao Kan, Yixiong Liang, and Jianxin Wang, “FedMMR: Multi-Modal Federated Learning Via Missing Modality Reconstruction,” in IEEE International Conference on Multimedia and Expo (ICME), 2024. (Accept)
[5] Qing Liu, Hailong Zeng, Zhaodong Sun, Xiaobai Li, Guoying Zhao, and Yixiong Liang, “Many Birds, One Stone: Medical Image Segmentation with Multiple Partially Labelled Datasets,” Pattern Recognition, p. 110636, 2024.
[6] Hailong Zeng, Jianfeng Liu, and Yixiong Liang, “Task-Aware Transformer For Partially Supervised Retinal Fundus Image Segmentation,” in International Joint Conference on Neural Networks (IJCNN), 2024. (Accept)
[7] Bolei Chen, Siyi Lu, Ping Zhong, Yongzheng Cui, Yixiong Liang, and Jianxin Wang, “SemNav-HRO: A Target-Driven Semantic Navigation Strategy with Human-Robot-Object Ternary Fusion,” Engineering Applications of Artificial Intelligence, vol. 127, p. 107370, Jan. 2024.
[8] Bolei Chen, Jiaxu Kang, Ping Zhong, Yongzheng Cui, Siyi Lu, Yixiong Liang, and Jianxin Wang, “Think Holistically, Act Down-to-Earth: A Semantic Navigation Strategy with Continuous Environmental Representation and Multi-step Forward Planning,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 34, no. 5, pp. 3860–3875, 2024.
[9] Chaojun Zhang, Yixiong Liang, and Qing Liu, “CCBox: Improving Box-Supervised Nuclei Segmentation with Consistency Constraint,” in IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2023, pp. 2412–2415.
[10] Shengqi Li, Qing Liu, Chaojun Zhang, and Yixiong Liang, “Adaptive Cluster Assignment for Unsupervised Semantic Segmentation,” in Chinese Conference on Pattern Recognition and Computer Vision (PRCV), 2023, pp. 75--86.
[11] Hulin Kuang, Yahui Wang, Yixiong Liang, Jin Liu, and Jianxin Wang, “BEA-Net: Body and Edge Aware Network with Multi-Scale Short-Term Concatenation for Medical Image Segmentation,” IEEE Journal of Biomedical and Health Informatics, vol. 27, no. 10, pp. 4828–4839, 2023.
[12] Lele Lv, Qing Liu, Shichao Kan, and Yixiong Liang, “Confidence-Aware Contrastive Learning for Semantic Segmentation,” in ACM international conference on Multimedia (ACM MM), 2023, pp. 5584–5593.
[13] Haotian Liu, Qing Liu, Yang Liu, Yixiong Liang, and Guoying Zhao, “Exploring Effective Knowledge Distillation for Tiny Object Detection,” in IEEE International Conference on Image Processing (ICIP), 2023, pp. 770–774.
[14] Bolei Chen, Ping Zhong, Yongzheng Cui, Siyi Lu, Yixiong Liang, and Yu Sheng, “EMExplorer: An Episodic Memory Enhanced Autonomous Exploration Strategy with Voronoi Domain Conversion and Invalid Action Masking,” Complex & Intelligent Systems, pp. 1–15, 2023.
[15] Tao Sheng, Chengchao Shen, Yuan Liu, Yeyu Ou, Zhe Qu, Yixiong Liang, and Jianxin Wang, “Modeling Global Distribution for Federated Learning with Label Distribution Skew,” Pattern Recognition, p. 109724, 2023.
[16] Yixiong Liang, Shuo Feng, Qing Liu, Hulin Kuang, Jianfeng Liu, Liyan Liao, Yun Du, and Jianxin Wang, “Exploring Contextual Relationships for Cervical Abnormal Cell Detection,” IEEE Journal of Biomedical and Health Informatics, vol. 27, no. 8, pp. 4086–4097, May 2023.
[17] Bolei Chen, Yongzheng Cui, Ping Zhong, Wang yang, Yixiong Liang, and Jianxin Wang, “STExplorer: A Hierarchical Autonomous Exploration Strategy with Spatio-Temporal Awareness for Aerial Robots,” ACM Transactions on Intelligent Systems and Technology, May 2023.
[18] Yixiong Liang, Zhihua Yin, Haotian Liu, Hailong Zeng, Jianxin Wang, Jianfeng Liu, and Nanying Che, “Weakly Supervised Deep Nuclei Segmentation with Sparsely Annotated Bounding Boxes for DNA Image Cytometry,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 20, no. 1, pp. 785–795, 2023.
[19] Qing Liu, Haotian Liu, Wei Ke, and Yixiong Liang, “Automated Lesion Segmentation in Fundus Images with Many-to-Many Reassembly of Features,” Pattern Recognition, vol. 136, p. 109191, 2023.
[20] Shichao Kan, Yixiong Liang, Min Li, Yigang Cen, Jianxin Wang, and Zhihai He, “Coded Residual Transform for Generalizable Deep Metric Learning,” in Advances in Neural Information Processing Systems (NeurIPS), 2022.
[21] Qing Liu, Haotian Liu, Yang Zhao, and Yixiong Liang, “Dual-Branch Network with Dual-Sampling Modulated Dice Loss for Hard Exudate Segmentation in Color Fundus Images,” IEEE Journal of Biomedical and Health Informatics, vol. 26, no. 3, pp. 1091–1102, 2022.
[22] Ping Zhong, Bolei Chen, Siyi Lu, Xiaoxi Meng, and Yixiong Liang, “Information-Driven Fast Marching Autonomous Exploration with Aerial Robots,” IEEE Robotics and Automation Letters, vol. 7, no. 2, pp. 810–817, 2022.
[23] Yongsheng Zhang, Qing Liu, Yang Zhao, and Yixiong Liang, “MEJIGCLU: More Effective Jigsaw Clustering For Unsupervised Visual Representation Learning,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022, pp. 2135–2139.
[24] Ruixiang Geng, Qing Liu, Shuo Feng, and Yixiong Liang, “Learning Deep Pathological Features for WSI-Level Cervical Cancer Grading,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022, pp. 1391–1395.
[25] Yao Xiang, Zhujun He, Qing Liu, Jialin Chen, and Yixiong Liang, “Autofocus of Whole Slide Imaging Based on Convolution and Recurrent Neural Networks,” Ultramicroscopy, vol. 220, p. 113146, 2021.
[26] Hulin Kuang, Yixiong Liang, Ning Liu, Jin Liu, and Jianxin Wang, “BEA-SegNet: body and edge aware network for medical image segmentation,” in IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2021, pp. 939–944.
[27] Yixiong Liang, Changli Pan, Wanxin Sun, Qing Liu, and Yun Du, “Global Context-Aware Cervical Cell Detection with Soft Scale Anchor Matching,” Computer Methods and Programs in Biomedicine, p. 106061, 2021.
[28] Yixiong Liang, Zhihong Tang, Meng Yan, Jialin Chen, Qing Liu, and Yao Xiang, “Comparison Detector for Cervical Cell/Clumps Detection in the Limited Data Scenario,” Neurocomputing, vol. 437, pp. 195–205, 2021.
[29] Yao Xiang, Wanxin Sun, Changli Pan, Meng Yan, Zhihua Yin, and Yixiong Liang, “A Novel Automation-Assisted Cervical Cancer Reading Method Based on Convolutional Neural Network,” Biocybernetics and Biomedical Engineering, vol. 40, no. 2, pp. 611–623, 2020.
[30] Qing Liu, Beiji Zou, Yang Zhao, and Yixiong Liang, “A Deep Gradient Boosting Network for Optic Disc and Cup Segmentation,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020, pp. 971–975.
[31] Meng Yan, Qing Liu, Zhihua Yin, Du Wang, and Yixiong Liang, “A Bidirectional Context Propagation Network for Urine Sediment Particle Detection in Microscopic Images,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020, pp. 981–985.
[32] Yao Xiang, Jialin Chen, Qing Liu, and Yixiong Liang, “Disentangled Representation Learning Based Multidomain Stain Normalization For Histological Images,” in IEEE International Conference on Image Processing (ICIP), 2020, pp. 360–364.
[33] Yixiong Liang, Meng Yan, Zhihong Tang, Zhujun He, and Jianfeng Liu, “Learning to Autofocus Based on Gradient Boosting Machine for Optical Microscopy,” Optik, vol. 198, p. 163002, 2019.
[34] Yingjun Jiang, Jianxin Wang, Yixiong Liang, and Jiazhi Xia, “Combining Static and Dynamic Features for Real-Time Moving Pedestrian Detection,” Multimedia Tools and Applications, vol. 78, no. 3, pp. 3781–3795, 2019.
[35] Yixiong Liang, Yuan Mao, Jiazhi Xia, Yao Xiang, and Jianfeng Liu, “Scale-Invariant Structure Saliency Selection for Fast Image Fusion,” Neurocomputing, vol. 356, no. 9, pp. 119–130, 2019.
[36] Yixiong Liang, Yuan Mao, Zhihong Tang, Meng Yan, Yuqian Zhao, and Jianfeng Liu, “Efficient Misalignment-Robust Multi-Focus Microscopical Images Fusion,” Signal Processing, vol. 161, no. 8, pp. 111–123, 2019.
工作经历
[1] 2019.2-至今
中南大学计算机学院
|
计算机科学与技术系
[2] 2007.7-2019.1
中南大学信息科学与工程学院
|
计算机科学与技术系
[3] 2011.7-2012.7
Carnegie Mellon University
|
The Robotics Institute
[4] 2005.7-2007.6
中国科学院自动化研究所
研究方向
其他联系方式
[1] 邮编：
团队成员
团队名称：计算机视觉&智能机器人
团队介绍：https://github.com/CVIU-CSU/PaperReading