中文版 | English

在结果中检索

CASIA OpenIR

浏览/检索结果: 共75条，第1-10条 帮助

已选(0)清除 条数/页：   排序方式：
Physical Contacts Between Mitochondria and WPBs Participate in WPB Maturation 期刊论文
ARTERIOSCLEROSIS THROMBOSIS AND VASCULAR BIOLOGY, 2024, 卷号: 44, 期号: 1, 页码: 108-123
作者:  Ma, Jing;  Hao, Zhenhua;  Zhang, Yudong;  Li, Liuju;  Huang, Xiaoshuai;  Wang, Yu;  Chen, Liangyi;  Yang, Ge;  Li, Wei
收藏  |  浏览/下载：4/0  |  提交时间：2024/07/03
endothelial cells  mitochondrion  organelle interaction  von Willebrand factor  Weibel-Palade body  
Design and Construction of a Spherical Magnet Array for Multi-dimensional Tactile Perception 会议论文
, Datong, China, 17-20 July 2023
作者:  Mei-Jiang Gui;  Xiao-Hu Zhou;  Xiao-Liang Xie;  Shi-Qi Liu;  Zhen-Qiu Feng;  Hao Li;  Tian-Yu Xiang;  De-Xing Huang;  Bo-Xian Yao;  Zeng-Guang Hou
Adobe PDF(1848Kb)  |  收藏  |  浏览/下载：20/7  |  提交时间：2024/06/25
Highly Interpretable Representation for Multi-Dimensional Tactile Perception 期刊论文
IEEE Transactions on Medical Robotics and Bionics, 2024, 卷号: 6, 期号: 1, 页码: 340-350
作者:  Mei-Jiang Gui;  Xiao-Hu Zhou;  Xiao-Liang Xie;  Shi-Qi Liu;  Zhen-Qiu Feng;  Hao Li;  Tian-Yu Xiang;  De-Xing Huang;  Bo-Xian Yao;  Yong-Gen Ling;  Zeng-Guang Hou
Adobe PDF(8895Kb)  |  收藏  |  浏览/下载：21/5  |  提交时间：2024/06/25
Digital Twin Driven Measurement in Robotic Flexible Printed Circuit Assembly 期刊论文
IEEE Transactions on Instrumentation & Measurement, 2023, 卷号: 72, 页码: 5007812
作者:  Yang Minghao;  Huang Zhenping;  Sun Yangchang;  Zhao Yongjia;  Sun Ruize;  Sun Qi;  Chen JinLong;  Qiang BaoHua;  Wang JingHong;  Sun FuChun
Adobe PDF(39985Kb)  |  收藏  |  浏览/下载：25/6  |  提交时间：2024/06/24
Fast Noninvasive Morphometric Characterization of Free Human Sperms Using Deep Learning 期刊论文
Microscopy and Microanalysis, 2022, 卷号: 28, 期号: 5, 页码: 1767-1779
作者:  Guole Liu;  Hao Shi;  Huan Zhang;  Yating Zhou;  Yujiao Sun;  Wei Li;  Xuefeng Huang;  Yuqiang Jiang;  Yaliang Fang;  Ge Yang
Adobe PDF(1167Kb)  |  收藏  |  浏览/下载：31/13  |  提交时间：2024/06/11
bright-field microscopy  deep learning  human sperm  intracytoplasmic sperm injection  sperm morphology  
A LiDAR Point Clouds Dataset of Ships in a Maritime Environment 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 7, 页码: 1681-1694
作者:  Qiuyu Zhang;  Lipeng Wang;  Hao Meng;  Wen Zhang;  Genghua Huang
Adobe PDF(10728Kb)  |  收藏  |  浏览/下载：40/15  |  提交时间：2024/06/07
3D point clouds dataset  dynamic tail wave  fog simulation  rainy simulation  simulated data  
Robust Motion Learning for Musculoskeletal Robots Based on a Recurrent Neural Network and Muscle Synergies 期刊论文
IEEE Transactions on Automation Science and Engineering, 2024, 页码: 1-16
作者:  Jiahao Chen;  Wu YX(吴亚雄);  Yao CJ(姚超竞);  Huang X(黄销)
Adobe PDF(4084Kb)  |  收藏  |  浏览/下载：46/9  |  提交时间：2024/06/04
Musculoskeletal system  Robots  Muscles  Reinforcement learning  Robustness  Learning systems  Recurrent neural networks  Musculoskeletal robots  recurrent neural network  muscle synergy  robustness  
Multi-Interface Strain Transfer Modeling for Flexible Endoscope Shape Sensing 期刊论文
IEEE ROBOTICS AND AUTOMATION LETTERS, 2024, 卷号: 9, 期号: 3, 页码: 2670-2677
作者:  Liu, Xinran;  Chen, Jian;  Hu, Jian;  Chen, Hao;  Huang, Yuanrui;  Liu, Hongbin
Adobe PDF(2488Kb)  |  收藏  |  浏览/下载：35/9  |  提交时间：2024/05/30
Sensors  Shape  Optical fiber sensors  Strain  Endoscopes  Robot sensing systems  Optical fibers  Surgical robotics: laparoscopy  soft sensors and actuators  surgical robotics: steerable catheters/needles  
Learning Realistic and Reasonable Grasps for Anthropomorphic Hand in Cluttered Scenes 会议论文
, Yokohama, Japan, 2024-5-13
作者:  Duan, Haonan;  Li, Yiming;  LI, Daheng;  Wei, Wei;  Huang, Yayu;  Wang, Peng
Adobe PDF(4993Kb)  |  收藏  |  浏览/下载：49/20  |  提交时间：2024/05/29
Robotic grasping  Anthropomorphic hand  Affordance  
Robotics Dexterous Grasping: The Methods Based on Point Cloud and Deep Learning 期刊论文
Frontiers in Neurorobotics, 2021, 卷号: 15, 页码: 658280
作者:  Duan, Haonan;  Wang, Peng;  Huang, Yayu;  Xu, Guangyun;  Wei, Wei;  Shen, Xiaofei
Adobe PDF(3145Kb)  |  收藏  |  浏览/下载：36/11  |  提交时间：2024/05/29
Robotics  Dexterous grasping  Point Cloud  Deep learning