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Improved Video Emotion Recognition with Alignment of CNN and Human Brain Representations 期刊论文
IEEE Transactions on Affective Computing, 2023, 页码: 1-15
作者:  Fu, Kaicheng;  Du, Changde;  Wang, Shengpei;  He, Huiguang
Adobe PDF(3907Kb)  |  收藏  |  浏览/下载：65/22  |  提交时间：2024/05/28
CNN-brain Alignment  Brain-guided Deep Learning  Video Emotion Recognition  Representation Similarity Analysis  
Large-scale Multi-modal Pre-trained Models: A Comprehensive Survey 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 4, 页码: 447-482
作者:  Xiao Wang;  Guangyao Chen;  Guangwu Qian;  Pengcheng Gao;  Xiao-Yong Wei;  Yaowei Wang;  Yonghong Tian;  Wen Gao
Adobe PDF(3540Kb)  |  收藏  |  浏览/下载：60/13  |  提交时间：2024/04/23
Multi-modal (MM), pre-trained model (PTM), information fusion, representation learning, deep learning  
VLP: A Survey on Vision-language Pre-training 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 1, 页码: 38-56
作者:  Fei-Long Chen;  Du-Zhen Zhang;  Ming-Lun Han;  Xiu-Yi Chen;  Jing Shi;  Shuang Xu;  Bo Xu
Adobe PDF(1427Kb)  |  收藏  |  浏览/下载：54/17  |  提交时间：2024/04/23
Vision and language  pre-training  transformers  multimodal learning  representation learning  
Towards Prior Gap and Representation Gap for Long-tailed Recognition, Pattern Recognition 期刊论文
Pattern Recognition, 2023, 卷号: 133, 期号: 109012, 页码: 109012
作者:  Zhang Ming-Liang;  Zhang Xu-Yao;  Wang Chang;  Liu Cheng-Lin
Adobe PDF(2258Kb)  |  收藏  |  浏览/下载：122/30  |  提交时间：2024/04/03
Long-tailed learning  Prior gap  Representation gap  Image recognition  
Clustering Enhanced Multiplex Graph Contrastive Representation Learning 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2023, 页码: 15
作者:  Yuan, Ruiwen;  Tang, Yongqiang;  Wu, Yajing;  Zhang, Wensheng
收藏  |  浏览/下载：59/0  |  提交时间：2024/03/27
Contrastive learning  graph representation learning  multiplex graph  multiview graph clustering  
Temporal Action Proposal Generation With Action Frequency Adaptive Network 期刊论文
IEEE Transactions on Multimedia, 2023, 卷号: 26, 页码: 2340 - 2353
作者:  Yepeng Tang;  Weining Wang;  Chunjie Zhang;  Jing Liu;  Yao Zhao
Adobe PDF(10095Kb)  |  收藏  |  浏览/下载：75/24  |  提交时间：2024/03/26
Proposals  Task analysis  Data models  Time-frequency analysis  Representation learning  Predictive models  Information science  Temporal action proposal generation  expert learning  fine-gained detection  action frequency  
Biphasic Face Photo-Sketch Synthesis via Semantic-Driven Generative Adversarial Network With Graph Representation Learning 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2023, 页码: 14
作者:  Qi, Xingqun;  Sun, Muyi;  Wang, Zijian;  Liu, Jiaming;  Li, Qi;  Zhao, Fang;  Zhang, Shanghang;  Shan, Caifeng
Adobe PDF(6718Kb)  |  收藏  |  浏览/下载：148/45  |  提交时间：2024/02/22
Face photo-sketch synthesis  generative adversarial network  graph representation learning  intraclass and interclass  iterative cycle training (ICT)  
Dual Structural Knowledge Interaction for Domain Adaptation 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2023, 卷号: 25, 页码: 9057-9070
作者:  Zuo, Yukun;  Yao, Hantao;  Zhuang, Liansheng;  Xu, Changsheng
收藏  |  浏览/下载：58/0  |  提交时间：2024/02/21
Manifolds  Feature extraction  Adaptation models  Representation learning  Task analysis  Semisupervised learning  Pattern recognition  Domain adaptation  structural knowledge  dual structural knowledge interaction  
Unsupervised Graph Representation Learning with Cluster-aware Self-training and Refining 期刊论文
ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY, 2023, 卷号: 14, 期号: 5, 页码: 21
作者:  Zhu, Yanqiao;  Xu, Yichen;  Yu, Feng;  Liu, Qiang;  Wu, Shu
Adobe PDF(1686Kb)  |  收藏  |  浏览/下载：103/5  |  提交时间：2023/12/21
Cluster-aware self-training and refining  unsupervised learning  graph representation learning  
Affine Subspace Robust Low-Rank Self-Representation: From Matrix to Tensor 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2023, 卷号: 45, 期号: 8, 页码: 9357-9373
作者:  Tang, Yongqiang;  Xie, Yuan;  Zhang, Wensheng
收藏  |  浏览/下载：87/0  |  提交时间：2023/11/17
Affine subspace  low-rank representation  low-rank tensor  multi-view learning  subspace clustering