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Instance segmentation of apple flowers using the improved mask R-CNN model 期刊论文
biosystems engineering, 2020, 期号: 193, 页码: 264-278
作者:  Tian YN(田雨农)
Adobe PDF(4718Kb)  |  收藏  |  浏览/下载：193/53  |  提交时间：2022/01/06
Apple flower images acquisition  Apple flower images acquisition  Deep learning  MASU R-CNN  Instance segmentation  
ESO-based controller with model predictive governor for 3D trajectory tracking of underactuated underwater vehicles 期刊论文
IEEE Transactions on Industrial Informatics, 2020, 期号: 17, 页码: 6114-6124
作者:  Kong SH(孔诗涵)
Adobe PDF(1569Kb)  |  收藏  |  浏览/下载：193/61  |  提交时间：2021/06/21
Underactuated underwater vehicle  model predictive control  robust control  3D trajectory tracking  extended state observer  
IWSCR: An intelligent water surface cleaner robot for collecting floating garbage 期刊论文
IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2020, 期号: 暂无, 页码: 暂无
作者:  Kong SH(孔诗涵)
Adobe PDF(1738Kb)  |  收藏  |  浏览/下载：211/49  |  提交时间：2021/06/21
Deep learning  grasping strategy  intelligent water surface cleaner  robot system  sliding-mode controller (SMC)  
Fixed-Time Sliding Mode Disturbance Observer-Based Nonsmooth Backstepping Control for Hypersonic Vehicles 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2020, 卷号: 50, 期号: 11, 页码: 4377-4386
作者:  Sun, Jinlin;  Yi, Jianqiang;  Pu, Zhiqiang;  Tan, Xiangmin
Adobe PDF(3197Kb)  |  收藏  |  浏览/下载：297/0  |  提交时间：2021/01/07
Backstepping  Disturbance observers  Backstepping  finite-time control  fixed-time observer  
Adaptive Fuzzy Nonsmooth Backstepping Output-Feedback Control for Hypersonic Vehicles With Finite-Time Convergence 期刊论文
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2020, 卷号: 28, 期号: 10, 页码: 2320-2334
作者:  Sun, Jinlin;  Yi, Jianqiang;  Pu, Zhiqiang;  Liu, Zhen
Adobe PDF(3972Kb)  |  收藏  |  浏览/下载：245/0  |  提交时间：2021/01/07
Backstepping  Adaptive fuzzy control  Fuzzy logic  finite-time control  fixed-time state observer  
Spatial Preserved Graph Convolution Networks for Person Re-identification 期刊论文
ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS, 2020, 卷号: 16, 期号: 1, 页码: 14
作者:  Li, Zhaoju;  Zhou, Zongwei;  Jiang, Nan;  Han, Zhenjun;  Xing, Junliang;  Jiao, Jianbin
Adobe PDF(937Kb)  |  收藏  |  浏览/下载：253/51  |  提交时间：2021/01/06
Person re-identification  graph convolution  feature embedding  
Engagement Enhancement Based on Human-in-the-Loop Optimization for Neural Rehabilitation 期刊论文
FRONTIERS IN NEUROROBOTICS, 2020, 卷号: 12, 期号: 无, 页码: 11
作者:  Wang, Jiaxing;  Wang, Weiqun;  Ren, Shixin;  Shi, Weiguo;  Hou, Zeng-Guang
Adobe PDF(2370Kb)  |  收藏  |  浏览/下载：354/82  |  提交时间：2021/01/06
human-in-the-loop optimization  EEG based neural engagement  sEMG based muscle activation  tracking accuracy  neural rehabilitation  
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: 13, 期号: 3, 页码: 657-667
作者:  Zhou, Yan-Jie;  Xie, Xiao-Liang;  Zhou, Xiao-Hu;  Liu, Shi-Qi;  Bian, Gui-Bin;  Hou, Zeng-Guang
Adobe PDF(2854Kb)  |  收藏  |  浏览/下载：358/96  |  提交时间：2020/11/05
Deep learning  Guidewire  X-ray fluoroscopy  Segmentation and localization  Robot-assisted intervention  
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;  Ruiqi,Li;  Zhenliang,Ni;  Shiqi,Liu;  Yan-Jie Zhou
浏览  |  Adobe PDF(2286Kb)  |  收藏  |  浏览/下载：335/70  |  提交时间：2020/11/05
Endovascular manipulations  multilayer and multimodal-fusion architecture (MMFA)  percutaneous coronary intervention (PCI),  technical skill assessment  
Skeleton-Based Action Recognition With Multi-Stream Adaptive Graph Convolutional Networks 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 期号: 29, 页码: 9532-9545
作者:  Shi, Lei;  Zhang, Yifan;  Cheng, Jian;  Lu, Hanqing
Adobe PDF(2849Kb)  |  收藏  |  浏览/下载：427/165  |  提交时间：2020/11/05
Skeleton-based action recognition, graph convolutional network, adaptive graph, multi-stream network.