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Feedback Convolutional Neural Network for Visual Localization and Segmentation 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2019, 卷号: 41, 期号: 7, 页码: 1627-1640
Authors:  Cao, Chunshui;  Huang, Yongzhen;  Yang, Yi;  Wang, Liang;  Wang, Zilei;  Tan, Tieniu
Favorite  |  View/Download:2/0  |  Submit date:2019/09/30
feedback  convolutional neural networks (CNNs)  weakly supervised  object localization  object segmentation  
GaitGANv2: Invariant gait feature extraction using generative adversarial networks 期刊论文
PATTERN RECOGNITION, 2019, 卷号: 87, 页码: 179-189
Authors:  Yu, Shiqi;  Liao, Rijun;  An, Weizhi;  Chen, Haifeng;  Garcia, Edel B.;  Huang, Yongzhen;  Poh, Norman
Favorite  |  View/Download:6/0  |  Submit date:2019/07/12
Gait recognition  Generative adversarial networks  Invariant feature  
A comprehensive study on gait biometrics via a joint CNN-based method 期刊论文
Pattern Recognition, 2019, 期号: 2019,93, 页码: 228-236
Authors:  Yuqi Zhang;  Yongzhen Huang;  Liang Wang;  Shiqi Yu
View  |  Adobe PDF(1248Kb)  |  Favorite  |  View/Download:59/23  |  Submit date:2019/04/30
Gait Recognition  Soft Biometrics  Joint Learning  Network Visualization  
A Review of Computational Intelligence for StarCraft AI 会议论文
, Bangalore, India, 18-21 Nov. 2018
Authors:  Tang, Zhentao;  Shao, Kun;  Zhu, Yuanheng;  Li, Dong;  Zhao, Dongbin;  Huang, Tingwen
View  |  Adobe PDF(131Kb)  |  Favorite  |  View/Download:48/34  |  Submit date:2019/04/25
A New Approach to Predict Progression-free Survival in Stage IV EGFR-mutant NSCLC Patients with EGFR-TKI Therapy 期刊论文
CLINICAL CANCER RESEARCH, 2018, 卷号: 24, 期号: 15, 页码: 3583-3592
Authors:  Song, Jiangdian;  Shi, Jingyun;  Dong, Di;  Fang, Mengjie;  Zhong, Wenzhao;  Wang, Kun;  Wu, Ning;  Huang, Yanqi;  Liu, Zhenyu;  Cheng, Yue;  Gan, Yuncui;  Zhou, Yongzhao;  Zhou, Ping;  Chen, Bojiang;  Liang, Changhong;  Liu, Zaiyi;  Li, Weimin;  Tian, Jie
Favorite  |  View/Download:46/0  |  Submit date:2018/10/10
Improving Deep Neural Network Based Speech Synthesis through Contextual Feature Parametrization and Multi-Task Learning 期刊论文
JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY, 2018, 卷号: 90, 期号: 7, 页码: 1025-1037
Authors:  Wen, Zhengqi;  Li, Kehuang;  Huang, Zhen;  Lee, Chin-Hui;  Tao, Jianhua;  Zhengqi Wen
View  |  Adobe PDF(995Kb)  |  Favorite  |  View/Download:81/24  |  Submit date:2018/01/05
Dnn-based Speech Synthesis  Vocoder  Speech Parametrization  Blstm  Phoneme Embedded Vector  Multi-task Learning  Pitch-scaled Spectrum  
In vivo CRISPR screening unveils histone demethylase UTX as an important epigenetic regulator in lung tumorigenesis 期刊论文
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2018, 卷号: 115, 期号: 17, 页码: E3978-E3986
Authors:  Wu, Qibiao;  Tian, Yahui;  Zhang, Jian;  Tong, Xinyuan;  Huang, Hsinyi;  Li, Shuai;  Zhao, Hong;  Tang, Ying;  Yuan, Chongze;  Wang, Kun;  Fang, Zhaoyuan;  Gao, Lei;  Hu, Xin;  Li, Fuming;  Qin, Zhen;  Yao, Shun;  Chen, Ting;  Chen, Haiquan;  Zhang, Gong;  Liu, Wanting;  Sun, Yihua;  Chen, Luonan;  Wong, Kwok-Kin;  Ge, Kai;  Chen, Liang;  Ji, Hongbin
Favorite  |  View/Download:50/0  |  Submit date:2018/10/10
Tumor Suppressor Genes  Crispr/cas9 In Vivo Knockout  Non-small Cell Lung Cancer  Utx  Ezh2 Inhibitor  
基于ACP行为动力学的犯罪主体行为平行建模分析 期刊论文
自动化学报, 2018, 卷号: 44, 期号: 2, 页码: 251-261
Authors:  刘烁;  王帅;  孟庆振;  叶佩军;  王涛;  黄文林;  王飞跃
View  |  Adobe PDF(4593Kb)  |  Favorite  |  View/Download:51/9  |  Submit date:2019/01/28
犯罪,主体行为建模,Acp方法,平行系统,行为动力学  
Deep Semantic Structural Constraints for Zero-Shot Learning 会议论文
, New Orleans, Louisiana, USA, 2018.2.2-2018.2.7
Authors:  Li Y(李岩);  Jia Z(贾真);  Zhang JG(张俊格);  Huang KQ(黄凯奇);  Tan TN(谭铁牛)
View  |  Adobe PDF(1739Kb)  |  Favorite  |  View/Download:325/102  |  Submit date:2018/01/03
Invariant feature extraction for gait recognition using only one uniform model 期刊论文
NEUROCOMPUTING, 2017, 卷号: 239, 页码: 81-93
Authors:  Yu, Shiqi;  Chen, Haifeng;  Wang, Qing;  Shen, Linlin;  Huang, Yongzhen
Favorite  |  View/Download:64/0  |  Submit date:2017/07/18
Gait Recognition  Deep Learning  Invariant Feature