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Fixed-time adaptive observer-based time-varying formation control for multi-agent systems with directed topologies 期刊论文
NEUROCOMPUTING, 2021, 卷号: 463, 页码: 483-494
作者:  Xiong, Tianyi;  Gu, Zhou;  Yi, Jianqiang;  Pu, Zhiqiang
收藏  |  浏览/下载：215/0  |  提交时间：2021/11/04
Directed topologies  Formation control  Fixed-time observer  Multi-agent systems  
A hybrid deep segmentation network for fundus vessels via deep-learning framework & nbsp; 期刊论文
NEUROCOMPUTING, 2021, 卷号: 448, 页码: 168-178
作者:  Yang, Lei;  Wang, Huaixin;  Zeng, Qingshan;  Liu, Yanhong;  Bian, Guibin
收藏  |  浏览/下载：272/0  |  提交时间：2021/08/15
Image segmentation  Fundus vessels  U-net network  Multitask segmentation network  Fusion network  
PrGCN: Probability prediction with graph convolutional network for person re-identification 期刊论文
NEUROCOMPUTING, 2021, 卷号: 423, 页码: 57-70
作者:  Liu, Hongmin;  Xiao, Zhenzhen;  Fan, Bin;  Zeng, Hui;  Zhang, Yifan;  Jiang, Guoquan
收藏  |  浏览/下载：223/0  |  提交时间：2021/03/08
Person re-identification  Graph convolutional network  Link probability prediction  Similarity measurement  
Estimation of human impedance and motion intention for constrained human-robot interaction 期刊论文
NEUROCOMPUTING, 2020, 卷号: 390, 页码: 268-279
作者:  Yu, Xinbo;  Li, Yanan;  Zhang, Shuang;  Xue, Chengqian;  Wang, Yu
收藏  |  浏览/下载：203/0  |  提交时间：2020/06/22
Human motion intention estimation  Impedance learning  Adaptive neural network control  Full-state constraints  Barrier Lyapunov functions  
Diffusion induced graph representation learning 期刊论文
NEUROCOMPUTING, 2019, 卷号: 360, 页码: 220-229
作者:  Li, Fuzhen;  Zhu, Zhenfeng;  Zhang, Xingxing;  Cheng, Jian;  Zhao, Yao
收藏  |  浏览/下载：220/0  |  提交时间：2019/12/16
Graph representation learning  Graph embedding  Diffusion model  Auto-encoder  Deep learning  
Adaptive neural control of quadruped robots with input deadzone 期刊论文
NEUROCOMPUTING, 2019, 卷号: 329, 页码: 486-494
作者:  Zhang, Shuang;  Zhang, Donghao;  Chang, Cheng;  Fu, Qiang;  Wang, Yu
收藏  |  浏览/下载：274/0  |  提交时间：2019/07/12
Quadruped robot  Neural networks  Input deadzone  Full state feedback  Output feedback