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Multitask Policy Adversarial Learning for Human-Level Control With Large State Spaces 期刊论文
IEEE Transactions on Industrial Informatics Information, 2019, 卷号: 15, 期号: 4, 页码: 2395-2404
作者:  Wang JP(王军平);  You Kang Shi;  Wen Sheng Zhang;  Ian Thomas;  Shi Hui Duan
Adobe PDF(2547Kb)  |  收藏  |  浏览/下载：112/39  |  提交时间：2023/05/05
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：169/56  |  提交时间：2021/06/18
Event co-reference resolution  Neural network  Information extraction  Multi-loss function  Event extraction  
Energy-Efficient IoT Service Composition for Concurrent Timed Applications 期刊论文
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2019, 2019, 2019, 2019, 2019, 卷号: 100, 100, 100, 100, 100, 页码: 1017-1030, 1017-1030, 1017-1030, 1017-1030, 1017-1030
作者:  Sun, Mengyu;  Zhou, Zhangbing;  Wang, Junping;  Du, Chu;  Gaaloul, Walid
Adobe PDF(1192Kb)  |  收藏  |  浏览/下载：250/44  |  提交时间：2020/03/30
IoT service composition  Temporal constraints  Concurrent requests  Energy efficiency  IoT service composition  Temporal constraints  IoT service composition  IoT service composition  IoT service composition  Concurrent requests  Temporal constraints  Temporal constraints  Temporal constraints  Energy efficiency  Concurrent requests  Concurrent requests  Concurrent requests  Energy efficiency  Energy efficiency  Energy efficiency  
A Survey of Discourse Representations for Chinese Discourse Annotation 期刊论文
ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING, 2019, 卷号: 18, 期号: 3, 页码: Article 26
作者:  Kang, Xiaomian;  Zong, Chengqing;  Xue, Nianwen
Adobe PDF(1801Kb)  |  收藏  |  浏览/下载：264/58  |  提交时间：2020/03/30
discourse representation  discourse theory  discourse structure  discourse analysis  
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：205/33  |  提交时间：2020/03/30
Visual tracking  bibliographic analysis  collaboration patterns  research hotspots  parallel vision  
A topic enhanced approach to detecting multiple standpoints in web texts 期刊论文
INFORMATION SCIENCES, 2019, 卷号: 501, 页码: 483-494
作者:  Lin, Junjie;  Kong, Qingchao;  Mao, Wenji;  Wang, Lei
浏览  |  Adobe PDF(1004Kb)  |  收藏  |  浏览/下载：338/93  |  提交时间：2019/10/08
Multiple standpoint detection  Topic model  Topic enhanced approach  Adaptive parameter determination  
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：336/29  |  提交时间：2019/09/30
Traffic prediction  Deep learning  Detrending  Multi-scale traffic prediction  
Weakly Semantic Guided Action Recognition 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2019, 卷号: 21, 期号: 10, 页码: 2504-2517
作者:  Yu, Tingzhao;  Wang, Lingfeng;  Da, Cheng;  Gu, Huxiang;  Xiang, Shiming;  Pan, Chunhong
浏览  |  Adobe PDF(18774Kb)  |  收藏  |  浏览/下载：440/113  |  提交时间：2019/05/15
Semantic guided module  action recognition  cross domain  3D convolution  attention model  
Decision Controller for Object Tracking With Deep Reinforcement Learning 期刊论文
IEEE ACCESS, 2019, 卷号: 7, 页码: 28069-28079
作者:  Zhong, Zhao;  Yang, Zichen;  Feng, Weitao;  Wu, Wei;  Hu, Yangyang;  Liu, Cheng-Lin
浏览  |  Adobe PDF(2984Kb)  |  收藏  |  浏览/下载：599/201  |  提交时间：2019/04/30
Computer vision  deep learning  object tracking  reinforcement learning