教授
所在单位:计算机学院
学历:博士研究生毕业
办公地点:中南大学新校区信息大楼
性别:男
联系方式:QQ:6532695
学位:博士学位
在职信息:在职
毕业院校:重庆大学
学科:计算机科学与技术
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[21]刘晴, 梁毅雄, 邹北骥, 赵杨.A Deep Gradient Boosting Network for Optic Disc and Cup Segmentation[C].ICASSP (CCF B类会议), 2020
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[22]严勐, 刘晴, 梁毅雄, 尹志华, 王都.A Bidirectional Context Propagation Network for Urine Sediment Particle Detection in Microscopic Images[C].ICASSP (CCF B类会议), 2020
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[23]向遥, 梁毅雄, 孙婉欣, 潘长立, 严勐, 尹志华.A novel automation-assisted cervical cancer reading method based on convolutional neural network[J].Biocybernetics and Biomedical Engineering, 2020, 40 (2) : 611-623.
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[24]梁毅雄, 刘剑锋, 毛渊, 唐志鸿, 严勐, 赵于前.Efficient Misalignment-Robust Multi-Focus Microscopical Images Fusion[J].Signal Processing, 2019, 161 (8) : 111-123.
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[25]梁毅雄, 刘剑锋, 毛渊, 夏佳志, 向遥.Scale-Invariant Structure Saliency Selection for Fast Image Fusion[J].Neurocomputing, 2019, 356 (7) : 119-130.
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[26]梁毅雄, 刘剑锋, 严勐, 唐志鸿, 何柱君.Learning to autofocus based on gradient boosting machine for optical microscopy[J].International Journal for Light and Electron Optic, 2019, 198 (12) : 163002.
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[27]梁毅雄, 康瑞, 连春燕, 毛渊.An End-to-End System for Automatic Urinary Particle Recognition with Convolutional Neural Network[J].Journal of medical systems, 2018, 42 (9) : 165.
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[28]梁毅雄, 刘剑锋, 唐志鸿, 严勐.Object detection based on deep learning for urine sediment examination[J].Biocybernetics and Biomedical Engineering, 2018, 38: 661-670.
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[29]梁毅雄, 廖胜辉, 王磊, 邹北骥.Exploring regularized feature selection for person specific face verification[C].ICCV (CCF A类会议), 2011: 1676-1683.
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[30]梁毅雄, Lei Wang, Shenghui Liao, Beiji Zou.Feature selection via simultaneous sparse approximation for person specific face verification[C].ICIP (CCF C类会议), 2011: 789-792.
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[31]梁毅雄, 刘凌波, 徐莹, 向遥, 邹北骥.Multitask GLOH feature selection for human age estimation[C].ICIP (CCF C类会议), 2011: 565-568.
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[32]梁毅雄, Chengrong Li, Weiguo Gong, Yingjun Pan.Uncorrelated linear discriminant analysis based on weighted pairwise fisher criterion[J].Pattern Recognition, 2007, 40 (12) : 3606-3615.
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[33]梁毅雄, Weiguo Gong, Yingjun Pan, Weihong Li.Generalizing relevance weighted LDA[J].Pattern Recognition, 2005, 38 (11) : 2217-2219.