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High-speed rail pole number recognition through deep representation and temporal redundancy 期刊论文
NEUROCOMPUTING, 2020, 卷号: 415, 页码: 201-214
作者:  Yang, Yang;  Zhang, Wensheng;  He, Zewen;  Li, Ding
Adobe PDF(2751Kb)  |  收藏  |  浏览/下载：318/58  |  提交时间：2021/01/07
Region-based convolutional neural network  Context information  Object detection  Number recognition  Pole number  High-speed rail  
CADN: A weakly supervised learning-based category-aware object detection network for surface defect detection 期刊论文
Pattern Recognition, 2020, 卷号: 109, 期号: 0, 页码: 10
作者:  Zou W(邹伟)
浏览  |  Adobe PDF(1839Kb)  |  收藏  |  浏览/下载：175/50  |  提交时间：2020/10/22
Weakly supervised learning, Automated surface inspection, Defect detection, Knowledge distillation  
Joint Learning in the Spatio-Temporal and Frequency Domains for Skeleton-Based Action Recognition 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2020, 卷号: 22, 期号: 9, 页码: 2207-2220
作者:  Guyue, Hu;  Bo, Cui;  Shan, Yu
Adobe PDF(4803Kb)  |  收藏  |  浏览/下载：327/64  |  提交时间：2020/09/28
Skeleton-based Action Recognition  Frequency Attention  Synchronous Local and Non-local Learning  Soft-margin Focal Loss  Pesudo Multi-task Learning  
Changes of Effective Connectivity in the Alpha Band Characterize Differential Processing of Audiovisual Information in Cross-Modal Selective Attention 期刊论文
NEUROSCIENCE BULLETIN, 2020, 卷号: 36, 期号: 9, 页码: 1009-1022
作者:  Niu, Weikun;  Jiang, Yuying;  Zhang, Xin;  Jiang, Tianzi;  Zhang, Yujin;  Yu, Shan
Adobe PDF(3941Kb)  |  收藏  |  浏览/下载：273/0  |  提交时间：2020/08/24
Human EEG  Audiovisual selective attention  Granger Causality  Pattern classification  
Multi-channel EEG recording during motor imagery of different joints from the same limb 期刊论文
SCIENTIFIC DATA, 2020, 卷号: 7, 期号: 1, 页码: 9
作者:  Ma, Xuelin;  Qiu, Shuang;  He, Huiguang
浏览  |  Adobe PDF(3879Kb)  |  收藏  |  浏览/下载：363/72  |  提交时间：2020/08/03
brain-computer interface, motor imagery, same limb  
Visual Defect Inspection for Deep-Aperture Components With Coarse-to-Fine Contour Extraction 期刊论文
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2020, 卷号: 69, 期号: 6, 页码: 3262-3274
作者:  Gong, Xinyi;  Su, Hu;  Xu, De;  Zhang, Jiabin;  Zhang, Lei;  Zhang, Zhengtao
浏览  |  Adobe PDF(1324Kb)  |  收藏  |  浏览/下载：368/78  |  提交时间：2020/08/03
Coarse-fine positioning  deep-hole component  defect inspection  edge grouping  image processing  
Deep Learning for Virtual Histological Staining of Bright-Field Microscopic Images of Unlabeled Carotid Artery Tissue 期刊论文
MOLECULAR IMAGING AND BIOLOGY, 2020, 期号: 22, 页码: 1301-1309
作者:  Li, Dan;  Hui, Hui;  Zhang, Yingqian;  Tong, Wei;  Tian, Feng;  Yang, Xin;  Liu, Jie;  Chen, Yundai;  Tian, Jie
浏览  |  Adobe PDF(4159Kb)  |  收藏  |  浏览/下载：294/67  |  提交时间：2020/07/20
Virtual histological staining  Conditional generative adversarial network  Blind evaluation  Bright-field microscopic imaging  
Parallel Internet of Vehicles: ACP-Based System Architecture and Behavioral Modeling 期刊论文
IEEE INTERNET OF THINGS JOURNAL, 2020, 卷号: 7, 期号: 5, 页码: 3735-3746
作者:  Wang, Xiao;  Han, Shuangshuang;  Yang, Linyao;  Yao, Tingting;  Li, Lingxi
Adobe PDF(3157Kb)  |  收藏  |  浏览/下载：290/31  |  提交时间：2020/06/22
Cyber-physical-social system (CPSS)  parallel intelligence  parallel Internet of Vehicles (PIoV)  
Underwater Bioinspired Propulsion: From Inspection to Manipulation 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2020, 卷号: 67, 期号: 9, 页码: 7629-7638
作者:  Wang, Yu;  Wang, Rui;  Wang, Shuo;  Tan, Min;  Yu, Junzhi
浏览  |  Adobe PDF(3768Kb)  |  收藏  |  浏览/下载：386/85  |  提交时间：2020/06/22
Propulsion  Manipulators  Sports  Path planning  Underwater vehicles  Inspection  Bioinspired propulsion  coordinated control  underwater vehicle-manipulator system  underwater manipulation  
Joint Anchor-Feature Refinement for Real-Time Accurate Object Detection in Images and Videos 期刊论文
IEEE Transactions on Circuits and Systems for Video Technology, 2020, 卷号: 无, 期号: 无, 页码: 无
作者:  Chen, Xingyu;  Yu, Junzhi;  Kong, Shihan;  Wu, Zhengxing;  Wen, Li
浏览  |  Adobe PDF(4122Kb)  |  收藏  |  浏览/下载：254/60  |  提交时间：2020/06/08
Object detection  Neural networks  Computer vision  Deep learning