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Event Co-reference Resolution via a Multi-loss Neural Network without Using Argument Information 期刊论文
Science China Information Sciences, 2019, 卷号: 62, 期号: 11, 页码: 212101:1–212101:9
作者:  Xinyu Zuo;  Yubo Chen;  Kang Liu;  Jun Zhao
Adobe PDF(360Kb)  |  收藏  |  浏览/下载：172/58  |  提交时间：2021/06/18
Event co-reference resolution  Neural network  Information extraction  Multi-loss function  Event extraction  
PKGCN: prior knowledge enhanced graph convolutional network for graph-based semi-supervised learning 期刊论文
INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS, 2019, 卷号: 10, 期号: 11, 页码: 3115-3127
作者:  Yu, Shaowei;  Yang, Xuebing;  Zhang, Wensheng
浏览  |  Adobe PDF(1959Kb)  |  收藏  |  浏览/下载：308/42  |  提交时间：2020/03/30
Graph convolutional network  Semi-supervised learning  Prior knowledge  Node classification  
Progress and Outlook of Visual Tracking: Bibliographic Analysis and Perspective 期刊论文
IEEE ACCESS, 2019, 卷号: 7, 页码: 184581-184598
作者:  Liu, Yating;  Wang, Kunfeng;  Li, Xuesong;  Bai, Tianxiang;  Wang, Fei-Yue
Adobe PDF(4276Kb)  |  收藏  |  浏览/下载：207/33  |  提交时间：2020/03/30
Visual tracking  bibliographic analysis  collaboration patterns  research hotspots  parallel vision  
Learning graph structure via graph convolutional networks 期刊论文
PATTERN RECOGNITION, 2019, 卷号: 95, 期号: -, 页码: 308-318
作者:  Zhang, Qi;  Chang, Jianlong;  Meng, Gaofeng;  Xu, Shibiao;  Xiang, Shiming;  Pan, Chunhong
浏览  |  Adobe PDF(2475Kb)  |  收藏  |  浏览/下载：465/110  |  提交时间：2019/12/16
Deep learning  Graph convolutional neural networks  Graph structure learning  Changeable kernel sizes  
Deep Multi-Modality Adversarial Networks for Unsupervised Domain Adaptation 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2019, 卷号: 21, 期号: 9, 页码: 2419-2431
作者:  Ma, Xinhong;  Zhang, Tianzhu;  Xu, Changsheng
Adobe PDF(2142Kb)  |  收藏  |  浏览/下载：350/44  |  提交时间：2019/12/16
Unsupervised domain adaptation  triplet loss  stacked attention  multi-modality  social event recognition  
Dual L-1-Normalized Context Aware Tensor Power Iteration and Its Applications to Multi-object Tracking and Multi-graph Matching 期刊论文
INTERNATIONAL JOURNAL OF COMPUTER VISION, 2019, 期号: 128, 页码: 33
作者:  Hu, Weiming;  Shi, Xinchu;  Zhou, Zongwei;  Xing, Junliang;  Ling, Haibin;  Maybank, Stephen
Adobe PDF(6300Kb)  |  收藏  |  浏览/下载：679/222  |  提交时间：2019/12/16
Multi-dimensional assignment  Context  hyper-context aware tensor power iteration  Multi-object tracking  Multi-graph matching  
DeepTrend 2.0: A light-weighted multi-scale traffic prediction model using detrending 期刊论文
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2019, 卷号: 103, 页码: 142-157
作者:  Dai, Xingyuan;  Fu, Rui;  Zhao, Enmin;  Zhang, Zuo;  Lin, Yilun;  Wang, Fei-Yue;  Li, Li
Adobe PDF(5109Kb)  |  收藏  |  浏览/下载：338/29  |  提交时间：2019/09/30
Traffic prediction  Deep learning  Detrending  Multi-scale traffic prediction  
A2CMHNE: Attention-Aware Collaborative Multimodal Heterogeneous Network Embedding 期刊论文
ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS, 2019, 卷号: 15, 期号: 2, 页码: 1-17
作者:  Jun Hu;  Shengsheng Qian;  Quan Fang;  Xueliang Liu;  Changsheng Xu
浏览  |  Adobe PDF(4471Kb)  |  收藏  |  浏览/下载：262/78  |  提交时间：2019/09/26
Network Embedding  Multimodal  Heterogeneous Network  
An Online Multiview Learning Algorithm for PolSAR Data Real-Time Classification 期刊论文
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2019, 卷号: 12, 期号: 1, 页码: 302-320
作者:  Nie, Xiangli;  Ding, Shuguang;  Huang, Xiayuan;  Qiao, Hong;  Zhang, Bo;  Jiang, Zhong-Ping
浏览  |  Adobe PDF(16269Kb)  |  收藏  |  浏览/下载：401/77  |  提交时间：2019/07/12
Multiview learning  online classification  passive-aggressive (PA) algorithm  polarimetric synthetic aperture radar (PolSAR)  
Incorporating Multi-Level User Preference into Document-Level Sentiment Classification 期刊论文
ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING, 2019, 卷号: 18, 期号: 1, 页码: 17
作者:  Li, Junjie;  Li, Haoran;  Kang, Xiaomian;  Yang, Haitong;  Zong, Chenqing
Adobe PDF(956Kb)  |  收藏  |  浏览/下载：328/47  |  提交时间：2019/07/12
Sentiment classification  deep learning  user preference  hierarchical attention network