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Abnormalities in the structural covariance of emotion regulation networks in major depressive disorder 期刊论文
JOURNAL OF PSYCHIATRIC RESEARCH, 2017, 卷号: 84, 页码: 237-242
作者:  Wu, Huawang;  Sun, Hui;  Wang, Chao;  Yu, Lin;  Li, Yilan;  Peng, Hongjun;  Lu, Xiaobing;  Hu, Qingmao;  Ning, Yuping;  Jiang, Tianzi;  Xu, Jinping;  Wang, Jiaojian
收藏  |  浏览/下载：233/0  |  提交时间：2017/02/14
Major Depressive Disorder  Structural Covariance  Vbm  Gray Matter Volume  Emotion Regulation Network  
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：437/146  |  提交时间：2016/06/21
Biologically Inspired  Hierarchical Model  Key Components Learning  Semantic Description  
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：734/299  |  提交时间：2015/11/12
Horror Image Recognition  Context-aware Multi-instance Learning  Visual Saliency  
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：352/77  |  提交时间：2016/03/30
Hmax  Biologically Inspired  Feedforward  Saliency Map  Middle Level Patch Learning  Feature Encoding  Multiclass Categorization  
Neural correlates of top-down letter processing 期刊论文
NEUROPSYCHOLOGIA, 2010, 卷号: 48, 期号: 2, 页码: 636-641
作者:  Liu, Jiangang;  Li, Jun;  Zhang, Hongchuan;  Rieth, Cory A.;  Huber, David E.;  Li, Wu;  Lee, Kang;  Tian, Jie
浏览  |  Adobe PDF(518Kb)  |  收藏  |  浏览/下载：313/80  |  提交时间：2015/08/12
Word Processing  Letter Processing  Top-down Processing  Fmri