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Distantsupervisionforrelationextractionwithhierarchicalselective attention 期刊论文
NeuralNetworks, 2018, 期号: 108, 页码: 240-247
作者:  Peng Zhou;  Jiaming Xu;  Zhenyu Qi;  Hongyun Bao;  Zhineng Chen;  Bo xu
浏览  |  Adobe PDF(663Kb)  |  收藏  |  浏览/下载：214/74  |  提交时间：2020/10/22
Relationextraction  Distantsupervision  Hierarchicalattention  Piecewiseconvolutionalneuralnetworks  
Empirical ExploringWord-Character Relationship for Chinese Sentence Representation 期刊论文
ACM Transactions on Asian and Low-Resource Language Information Processing, 2018, 卷号: 3, 期号: 17, 页码: 1-15
作者:  shaonan wang;  jiajun zhang;  chengqing zong
浏览  |  Adobe PDF(2098Kb)  |  收藏  |  浏览/下载：87/35  |  提交时间：2020/10/13
Sentence representation  composition model  
Toward a Maneuverable Miniature Robotic Fish Equipped With a Novel Magnetic Actuator System 期刊论文
IEEE Transactions on Systems Man Cybernetics-Systems, 2018, 卷号: 无, 期号: 无, 页码: 无
作者:  Chen, Xingyu;  Yu, Junzhi;  Wu, Zhengxing;  Meng, Yan;  Kong, Shihan
浏览  |  Adobe PDF(1707Kb)  |  收藏  |  浏览/下载：238/77  |  提交时间：2020/06/08
Dynamic modeling  Magnetic actuator system (MAS)  Maneuverability  Robotic fish  Underwater robot  
Broad Learning System: An Effective and Efficient Incremental Learning System Without the Need for Deep Architecture 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: 29, 期号: 1, 页码: 10-24
作者:  Chen, C. L. Philip;  Liu, Zhulin
收藏  |  浏览/下载：205/0  |  提交时间：2019/12/16
Big data  big data modeling  broad learning system (BLS)  deep learning  incremental learning  random vector functional-link neural networks (RVFLNN)  single layer feedforward neural networks (SLFN)  singular value decomposition (SVD)  
A High-Speed Seam Extraction Method Based on the Novel Structured-Light Sensor for Arc Welding Robot: A Review 期刊论文
IEEE SENSORS JOURNAL, 2018, 卷号: 18, 期号: 21, 页码: 8631-8641
作者:  Yang, Lei;  Li, En;  Long, Teng;  Fan, Junfeng;  Liang, Zize
Adobe PDF(2552Kb)  |  收藏  |  浏览/下载：260/24  |  提交时间：2019/12/16
Seam extraction  structured light vision  target tracking  KCF  
A Basal Ganglia Network Centric Reinforcement Learning Model and Its Application in Unmanned Aerial Vehicle 期刊论文
IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS, 2018, 卷号: 10, 期号: 2, 页码: 290-303
作者:  Zeng, Yi;  Wang, Guixiang;  Xu, Bo
收藏  |  浏览/下载：213/0  |  提交时间：2019/12/16
Basal ganglia (BG) network  brain-inspired intelligence  precise encoding  reinforcement learning model  unmanned aerial vehicle (UAV) autonomous learning  
MFR-CNN: Incorporating Multi-Scale Features and Global Information for Traffic Object Detection 期刊论文
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2018, 卷号: 67, 期号: 9, 页码: 8019-8030
作者:  Zhang, Hui;  Wang, Kunfeng;  Tian, Yonglin;  Gou, Chao;  Wang, Fei-Yue
Adobe PDF(4636Kb)  |  收藏  |  浏览/下载：308/60  |  提交时间：2019/12/16
Traffic Object Detection  Convolutional Neural Network  Multi-scale Features  Global Information  
Parallel Crime Scene Analysis Based on ACP Approach 期刊论文
IEEE Transactions on Computational Social Systems, 2018, 卷号: 5, 期号: 1, 页码: 244-255
作者:  Wang, Shuai;  Wang, Xiao;  Ye, Peijun;  Yuan, Yong;  Liu, Shuo;  Wang, Feiyue
Adobe PDF(2590Kb)  |  收藏  |  浏览/下载：271/77  |  提交时间：2019/11/12
Artificial Societies  Computational Experiments  Parallel Execution  Crime Scene Analysis  Parallel Systems  
Blockchain Powered Parallel Healthcare Systems Based on ACP Approach 期刊论文
IEEE Transactions on Computational Social Systems, 2018, 卷号: 5, 期号: 4, 页码: 942-950
作者:  Wang, Shuai;  Wang, Jing;  Wang, Xiao;  Qiu, Tianyu;  Yuan, Yong;  Ouyang, Liwei;  Guo, Yuanyuan;  Wang, Feiyue
Adobe PDF(1453Kb)  |  收藏  |  浏览/下载：291/74  |  提交时间：2019/11/12
Artificial Systems + Computational Experiments + Parallel Execution (Acp)  Blockchain  Parallel Healthcare Systems (Phss)  Parallel Intelligence  
Multiview Clustering via Unified and View-Specific Embeddings Learning 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: 29, 期号: 11, 页码: 5541-5553
作者:  Yin, Qiyue;  Wu, Shu;  Wang, Liang
收藏  |  浏览/下载：197/0  |  提交时间：2019/10/10
Incomplete multiview data  knowledge graph embedding  multiview learning  subspace learning