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基于磁共振成像的个体化脑功能和行为预测研究 学位论文
, 中国科学院自动化研究所: 中国科学院自动化研究所, 2019
Authors:  吴东亚
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脑结构连接  脑功能  人类行为  个体化预测  磁共振成像  
基于微惯性技术的行人航迹推演研究及位姿感知系统设计 学位论文
工学硕士, 中国科学院自动化研究所: 中国科学院研究生院, 2019
Authors:  吴源
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Imu  运动感知  航迹推演  室内定位  人机交互  Motion Perception  Pedestrian Dead-reckoning  Indoor Positioning  Human-computer Interaction  
ESI工程学领域热点论文推送2019年5月 其他
2019-05-27
Authors:  张桂英
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面向社交媒体的用户建模方法研究 学位论文
工学博士, 中国科学院自动化研究所: 中国科学院大学, 2019
Authors:  蔡驰宇
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社交媒体  用户建模  用户检测  跨平台  深度学习  
无权访问的条目 学位论文
Authors:  李康
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ESI工程学领域热点论文(2019年3月) 其他
2019-04-01
Authors:  张桂英
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Analysis of Interventionalists' Natural Behaviors for Recognizing Motion Patterns of Endovascular Tools During Percutaneous Coronary Interventions 期刊论文
IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS, 2019, 卷号: 13, 期号: 2, 页码: 330-342
Authors:  Zhou, Xiao-Hu;  Bian, Gui-Bin;  Xie, Xiao-Liang;  Hou, Zeng-Guang;  Qu, Xinkai;  Guan, Shaofeng
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Analysis framework  hidden Markov model  hierarchical classification framework  natural behaviors  percutaneous coronary intervention  
Analysis of Interventionalists' Natural Behaviors for Recognizing Motion Patterns of Endovascular Tools During Percutaneous Coronary Interventions 期刊论文
IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS, 2019, 卷号: 13, 期号: 2, 页码: 330-342
Authors:  Zhou Xiao-Hu;  Bian Gui-Bin;  Xie Xiao-Liang;  Hou Zeng-Guang;  Qu Xin-Kai;  Guan Shao-Feng
View  |  Adobe PDF(2985Kb)  |  Favorite  |  View/Download:12/3  |  Submit date:2019/04/24
Natural behaviors, percutaneous coronary intervention, hidden Markov model, analysis framework, hierarchical classification framework.  
Bioluminescence Tomography Based on Bilateral Weight Laplace method for In vivo Morphological Imaging of Glioma 会议论文
, San Francisco, USA, 2019.02.01
Authors:  Gao, Yuan;  Wang, Kun;  Meng, Hui;  An, Yu;  Jiang, Shixin;  Tian, Jie
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StarCraft Micromanagement With Reinforcement Learning and Curriculum Transfer Learning 期刊论文
IEEE Transactions on Emerging Topics in Computational Intelligence, 2019, 卷号: 3, 期号: 1, 页码: 73-84
Authors:  Kun Shao;  Yuanheng Zhu;  Dongbin Zhao
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Reinforcement Learning, Transfer Learning, Curriculum Learning, Neural Network, Game Ai