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A Control Framework for Adaptation of Training Task and Robotic Assistance for Promoting Motor Learning With an Upper Limb Rehabilitation Robot 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2022, 卷号: 52, 期号: 12, 页码: 7737-7747
作者:  Wang, Chen;  Peng, Liang;  Hou, Zeng-Guang
Adobe PDF(2528Kb)  |  收藏  |  浏览/下载：256/20  |  提交时间：2022/06/10
Robots  Trajectory  Task analysis  Training  Oscillators  Rehabilitation robotics  Real-time systems  Assist as needed (AAN)  motor learning  nonlinear adaptive control  rehabilitation robotics  
Kinematics, dynamics, and load distribution analysis of a 4-PPPS redundantly actuated parallel manipulator 期刊论文
MECHANISM AND MACHINE THEORY, 2022, 卷号: 167, 页码: 22
作者:  Liu, Zhaoyang;  Tao, Rui;  Fan, Junfeng;  Wang, Zhe;  Jing, Fengshui;  Tan, Min
Adobe PDF(2483Kb)  |  收藏  |  浏览/下载：292/17  |  提交时间：2021/11/04
Redundant parallel manipulator  Kinematics  Dynamics  Screw theory  Load distribution  
Improve Person Re-Identification With Part Awareness Learning 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 卷号: 29, 页码: 7468-7481
作者:  Huang, Houjing;  Yang, Wenjie;  Lin, Jinbin;  Huang, Guan;  Xu, Jiamiao;  Wang, Guoli;  Chen, Xiaotang;  Huang, Kaiqi
Adobe PDF(3927Kb)  |  收藏  |  浏览/下载：357/69  |  提交时间：2020/08/31
Person re-identification  part awareness  part segmentation  multi-task learning  
Instance segmentation of apple flowers using the improved mask R-CNN model 期刊论文
BIOSYSTEMS ENGINEERING, 2020, 卷号: 193, 页码: 264-278
作者:  Tian, Yunong;  Yang, Guodong;  Wang, Zhe;  Li, En;  Liang, Zize
Adobe PDF(4718Kb)  |  收藏  |  浏览/下载：418/114  |  提交时间：2020/06/02
Apple flower images acquisition  Image augmentation  Deep learning  MASU R-CNN  Instance segmentation  
Focal Boundary Guided Salient Object Detection 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2019, 卷号: 28, 期号: 6, 页码: 2813-2824
作者:  Wang, Yupei;  Zhao, Xin;  Hu, Xuecai;  Li, Yin;  Huang, Kaiqi
浏览  |  Adobe PDF(3275Kb)  |  收藏  |  浏览/下载：622/279  |  提交时间：2019/04/19
Visual saliency detection  salient object segmentation  boundary detection  deep learning