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Audio-driven Dubbing for User Generated Contents via Style-aware Semi-parametric Synthesis 期刊论文
IEEE Transactions on Circuits and Systems for Video Technology, 2022, 卷号: 33, 期号: 3, 页码: 1247 - 1261
作者:  Song LS(宋林森);  Wu WY(吴文岩);  Fu CY(傅朝友);  Loy, Chen Change;  He R(赫然)
Adobe PDF(8629Kb)  |  收藏  |  浏览/下载：155/61  |  提交时间：2023/06/29
Talking Face Generation  Video Generation  GAN  Thin-plate Spline  
DATA: Differentiable ArchiTecture Approximation 会议论文
, 加拿大, 2019.12
作者:  Chang, Jianlong
浏览  |  Adobe PDF(1035Kb)  |  收藏  |  浏览/下载：345/67  |  提交时间：2020/06/10
Disrupted topological organization of structural networks revealed by probabilistic diffusion tractography in Tourette syndrome children 期刊论文
HUMAN BRAIN MAPPING, 2017, 卷号: 38, 期号: 8, 页码: 3988-4008
作者:  Wen, Hongwei;  Liu, Yue;  Rekik, Islem;  Wang, Shengpei;  Zhang, Jishui;  Zhang, Yue;  Peng, Yun;  He, Huiguang;  He HG(何晖光)
Adobe PDF(938Kb)  |  收藏  |  浏览/下载：640/212  |  提交时间：2017/06/06
Tourette Syndrome  Diffusion Mri  Probabilistic Tractography  Structural Network  Graph Theory  Topological Organization  Multiple Kernel Learning  
Combining Disrupted and Discriminative Topological Properties of Functional Connectivity Networks as Neuroimaging Biomarkers for Accurate Diagnosis of Early Tourette Syndrome Children 期刊论文
MOLECULAR NEUROBIOLOGY, 2018, 卷号: 55, 期号: 4, 页码: 3251-3269
作者:  Wen, Hongwei;  Liu, Yue;  Rekik, Islem;  Wang, Shengpei;  Chen, Zhiqiang;  Zhang, Jishui;  Zhang, Yue;  Peng, Yun;  He, Huiguang;  He HG(何晖光)
浏览  |  Adobe PDF(6672Kb)  |  收藏  |  浏览/下载：650/199  |  提交时间：2017/06/06
Tourette Syndrome  Children  Functional Connectivity  Graph Theory  Topological Organization  Similarity Network Fusion  
Polygenic risk for five psychiatric disorders and cross-disorder and disorder-specific neural connectivity in two independent populations 期刊论文
NEUROIMAGE-CLINICAL, 2017, 卷号: 14, 期号: 14, 页码: 441-449
作者:  Wang, Tianqi;  Zhang, Xiaolong;  Li, Ang;  Zhu, Meifang;  Liu, Shu;  Qin, Wen;  Li, Jin;  Yu, Chunshui;  Jiang, Tianzi;  Liu, Bing
浏览  |  Adobe PDF(1182Kb)  |  收藏  |  浏览/下载：415/112  |  提交时间：2017/05/09
Polygenic Risk Score  Neural Connectivity  Cross-disorder  Disorder-specific  Fmri  
Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls 期刊论文
NEUROIMAGE, 2017, 卷号: 145, 页码: 137-165
作者:  Arbabshirani, Mohammad R.;  Plis, Sergey;  Sui, Jing;  Calhoun, Vince D.
Adobe PDF(2676Kb)  |  收藏  |  浏览/下载：492/124  |  提交时间：2017/02/14
Neuroimaging  Machine Learning  Classification  Brain Disorders  Prediction  
Multimedia News Summarization in Search 期刊论文
ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY, 2016, 卷号: 7, 期号: 3
作者:  Li, Zechao;  Tang, Jinhui;  Wang, Xueming;  Liu, Jing;  Lu, Hanqing
Adobe PDF(1304Kb)  |  收藏  |  浏览/下载：511/215  |  提交时间：2016/10/20
Design  Algorithms  Performance  Human Factors  News Summarization  Topic Structure  Multimodal  Hierarchical Latent Dirichlet Allocation  Maximum Spanning Tree  
Biologically Inspired Model for Visual Cognition Achieving Unsupervised Episodic and Semantic Feature Learning 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2016, 卷号: 46, 期号: 10, 页码: 2335-2347
作者:  Qiao, Hong;  Li, Yinlin;  Li, Fengfu;  Xi, Xuanyang;  Wu, Wei
浏览  |  Adobe PDF(2781Kb)  |  收藏  |  浏览/下载：488/162  |  提交时间：2016/06/21
Biologically Inspired  Hierarchical Model  Key Components Learning  Semantic Description  
Enhanced HMAX model with feedforward feature learning for multiclass categorization 期刊论文
FRONTIERS IN COMPUTATIONAL NEUROSCIENCE, 2015, 卷号: 9, 页码: 1-14
作者:  Li, Yinlin;  Wu, Wei;  Zhang, Bo;  Li, Fengfu
浏览  |  Adobe PDF(3664Kb)  |  收藏  |  浏览/下载：399/90  |  提交时间：2016/03/30
Hmax  Biologically Inspired  Feedforward  Saliency Map  Middle Level Patch Learning  Feature Encoding  Multiclass Categorization  
Horror Image Recognition Based on Context-Aware Multi-Instance Learning 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2015, 卷号: 24, 期号: 12, 页码: 5193-5205
作者:  Li, Bing;  Xiong, Weihua;  Wu, Ou;  Hu, Weiming;  Maybank, Stephen;  Yan, Shuicheng;  Bing Li
浏览  |  Adobe PDF(906Kb)  |  收藏  |  浏览/下载：798/315  |  提交时间：2015/11/12
Horror Image Recognition  Context-aware Multi-instance Learning  Visual Saliency