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浏览/检索结果: 共5条，第1-5条 帮助 限定条件 发表日期：2020     已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序 A Real-time Multi-functional Framework for Guidewire Morphological and Positional Analysis in Interventional X-ray Fluoroscopy 期刊论文 IEEE Transactions on Cognitive and Developmental Systems, 2020, 卷号: PP, 期号: 99, 页码: 1-1 作者:  Yanjie,Zhou;  Xiaoliang,Xie;  Xiaohu,Zhou;  Shiqi,Liu;  Guibin,Bian 收藏  |  浏览/下载：35/0  |  提交时间：2020/11/05 deep learning  guidewire  X-ray fluoroscopy  segmentation and localization  robot-assisted intervention   Learning impedance control of robots with enhanced transient and steady-state control performances 期刊论文 SCIENCE CHINA-INFORMATION SCIENCES, 2020, 卷号: 63, 期号: 9, 页码: 13 作者:  Sun, Tairen;  Cheng, Long;  Peng, Liang;  Hou, Zengguang;  Pan, Yongping 收藏  |  浏览/下载：6/0  |  提交时间：2020/09/07 robot  adaptive control  neural network  impedance control  parameter convergence   Learning Regional Attention Convolutional Neural Network for Motion Intention Recognition Based on EEG Data 会议论文 online in a virtual reality, January 7-15, 2021 作者:  Zhijie Fang;  Weiqun Wang;  Shixin Ren;  Jiaxing Wang;  Weiguo Shi 收藏  |  浏览/下载：26/0  |  提交时间：2021/06/16 A Multilayer and Multimodal-Fusion Architecture for Simultaneous Recognition of Endovascular Manipulations and Assessment of Technical Skills 期刊论文 IEEE TRANSACTIONS ON CYBERNETICS, 2020, 卷号: PP, 期号: 99, 页码: 1-13 作者:  Xiaohu,Zhou;  Xiaoliang.Xie;  Zhenqiu,Feng;  Zengguang,Hou;  Guibin,Bian 收藏  |  浏览/下载：20/0  |  提交时间：2020/11/05 Endovascular manipulations  multilayer and multimodal-fusion architecture (MMFA)  percutaneous coronary intervention (PCI),  technical skill assessment   Cross-Modality Paired-Images Generation and Augmentation for RGB-Infrared Person Re-Identification 期刊论文 Neural Networks, 2020, 卷号: 128, 期号: 128, 页码: 294-304 作者:  Guan'an Wangang;  Yang Yang;  Tianzhu Zhang;  Jian Cheng;  Zengguang Hou 收藏  |  浏览/下载：14/0  |  提交时间：2020/10/27 Person re-identification  Cross-modality  Feature disentanglement  Image generation  Adversarial learning