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Knowledge-driven Egocentric Multimodal Activity Recognition 期刊论文
ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS, 2020, 卷号: 16, 期号: 4, 页码: 21
作者:  Huang, Yi;  Yang, Xiaoshan;  Gao, Junyu;  Sang, Jitao;  Xu, Changsheng
Adobe PDF(1875Kb)  |  收藏  |  浏览/下载：424/67  |  提交时间：2021/03/08
Egocentric videos  wearable sensors  graph neural networks  
3D PostureNet: A unified framework for skeleton-based posture recognition 期刊论文
PATTERN RECOGNITION LETTERS, 2020, 卷号: 140, 期号: 140, 页码: 143-149
作者:  Liu, Jianbo;  Wang, Ying;  Liu, Yongcheng;  Xiang, Shiming;  Pan, Chunhong
Adobe PDF(1997Kb)  |  收藏  |  浏览/下载：295/44  |  提交时间：2021/03/02
Human posture recognition  Static hand gesture recognition  Skeleton-based  3D convolutional neural network  
Toward Improving Engagement in Neural Rehabilitation: Attention Enhancement Based on Brain-Computer Interface and Audiovisual Feedback 期刊论文
IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS, 2020, 卷号: 12, 期号: 4, 页码: 787-796
作者:  Wang, Jiaxing;  Wang, Weiqun;  Hou, Zeng-Guang
Adobe PDF(2031Kb)  |  收藏  |  浏览/下载：338/73  |  提交时间：2021/03/02
Avatars  Electroencephalography  Training  Games  Real-time systems  Task analysis  Stroke (medical condition)  Attention enhancement  brain–  computer interface (BCI)  electroencephalogram (EEG)  neural rehabilitation  virtual reality  
An Automatic Rehabilitation Assessment System for Hand Function Based on Leap Motion and Ensemble Learning 期刊论文
CYBERNETICS AND SYSTEMS, 2020, 页码: 23
作者:  Li, Chenguang;  Cheng, Long;  Yang, Hongjun;  Zou, Yongxiang;  Huang, Fubiao
Adobe PDF(2555Kb)  |  收藏  |  浏览/下载：321/45  |  提交时间：2021/01/07
Automatic assessment  Brunnstrom assessment  ensemble learning  Fugl-Meyer assessment  hand function assessment  rehabilitation  Leap Motion  
Long video question answering: A Matching-guided Attention Model 期刊论文
PATTERN RECOGNITION, 2020, 卷号: 102, 期号: 1, 页码: 11
作者:  Wang, Weining;  Huang, Yan;  Wang, Liang
浏览  |  Adobe PDF(1963Kb)  |  收藏  |  浏览/下载：393/79  |  提交时间：2020/06/02
Long video QA  Matching-guided attention