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Semantic and Temporal Contextual Correlation Learning for Weakly-Supervised Temporal Action Localization 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2023, 卷号: 45, 期号: 10, 页码: 12427-12443
作者:  Fu, Jie;  Gao, Junyu;  Xu, Changsheng
收藏  |  浏览/下载：61/0  |  提交时间：2023/11/16
Weakly-supervised  video  action localization  semantic  temporal context  correlation learning  
Multi-View Multi-Label Fine-Grained Emotion Decoding From Human Brain Activity 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 页码: 15
作者:  Fu, Kaicheng;  Du, Changde;  Wang, Shengpei;  He, Huiguang
Adobe PDF(4570Kb)  |  收藏  |  浏览/下载：230/59  |  提交时间：2022/12/27
Decoding  Brain modeling  Functional magnetic resonance imaging  Predictive models  Emotion recognition  Dimensionality reduction  Pattern recognition  Fine-grained emotion decoding  multi-label learning  multi-view learning  product of experts (PoEs)  variational autoencoder  
Learning Semantic-Aware Spatial-Temporal Attention for Interpretable Action Recognition 期刊论文
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2022, 卷号: 32, 期号: 8, 页码: 5213-5224
作者:  Fu, Jie;  Gao, Junyu;  Xu, Changsheng
收藏  |  浏览/下载：248/0  |  提交时间：2022/09/19
Visualization  Semantics  Task analysis  Three-dimensional displays  Feature extraction  Solid modeling  Predictive models  Semantic-aware  spatial-temporal attention  interpretable  action recognition  
Metadata Connector: Exploiting Hashtag and Tag for Cross-OSN Event Search 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2021, 卷号: 23, 页码: 510-523
作者:  Gao, Yuqi;  Sang, Jitao;  Fu, Chengpeng;  Wang, Zhengjia;  Ren, Tongwei;  Xu, Changsheng
收藏  |  浏览/下载：157/0  |  提交时间：2021/03/08
Twitter  Tagging  Videos  YouTube  Flickr  Games  Social media search  cross-OSN application  social multimedia  
Adaptive neural control of quadruped robots with input deadzone 期刊论文
NEUROCOMPUTING, 2019, 卷号: 329, 页码: 486-494
作者:  Zhang, Shuang;  Zhang, Donghao;  Chang, Cheng;  Fu, Qiang;  Wang, Yu
收藏  |  浏览/下载：232/0  |  提交时间：2019/07/12
Quadruped robot  Neural networks  Input deadzone  Full state feedback  Output feedback