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Reinforcement Learning in Process Industries: Review and Perspective 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 2, 页码: 283-300
作者:  Oguzhan Dogru;  Junyao Xie;  Om Prakash;  Ranjith Chiplunkar;  Jansen Soesanto;  Hongtian Chen;  Kirubakaran Velswamy;  Fadi Ibrahim;  Biao Huang
Adobe PDF(1275Kb)  |  收藏  |  浏览/下载：37/13  |  提交时间：2024/01/23
Process control  process systems engineering  reinforcement learning  
An Efficient and Robust Complex Weld Seam Feature Point Extraction Method for Seam Tracking and Posture Adjustment 期刊论文
IEEE Transactions on Industrial Informatics, 2023, 卷号: 19, 期号: 11, 页码: 10704 - 10715
作者:  Yunkai Ma;  Junfeng Fan;  Huizhen Yang;  Hongliang Wang;  Shiyu Xing;  Fengshui Jing;  Min Tan
Adobe PDF(9580Kb)  |  收藏  |  浏览/下载：172/44  |  提交时间：2023/10/08
Efficient Visual Recognition: A Survey on Recent Advances and Brain-inspired Methodologies 期刊论文
Machine Intelligence Research, 2022, 卷号: 19, 期号: 5, 页码: 366-411
作者:  Yang Wu;  Ding-Heng Wang;  Xiao-Tong Lu;  Fan Yang;  Man Yao;  Wei-Sheng Dong;  Jian-Bo Shi;  Guo-Qi Li
Adobe PDF(6780Kb)  |  收藏  |  浏览/下载：5/0  |  提交时间：2024/04/23
Visual recognition  deep neural networks (DNNS)  brain-inspired methodologies  network compression  dynamic inference  survey  
Enhanced Bounding Box Estimation with Distribution Calibration for Visual Tracking 期刊论文
SENSORS, 2021, 卷号: 21, 期号: 23, 页码: 14
作者:  Yu, Bin;  Tang, Ming;  Zhu, Guibo;  Wang, Jinqiao;  Lu, Hanqing
Adobe PDF(10825Kb)  |  收藏  |  浏览/下载：367/64  |  提交时间：2022/02/16
visual tracking  bounding box estimation  overlap maximization  distribution calibration  
Seam Feature Point Acquisition Based on Efficient Convolution Operator and Particle Filter in GMAW 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2021, 卷号: 17, 期号: 2, 页码: 1220-1230
作者:  Fan, Junfeng;  Deng, Sai;  Ma, Yunkai;  Zhou, Chao;  Jing, Fengshui;  Tan, Min
收藏  |  浏览/下载：229/0  |  提交时间：2021/03/02
Welding  Target tracking  Vision sensors  Feature extraction  Cameras  Robots  Convolution  Efficient convolution operator (ECO)  particle filter (PF)  robot intelligent welding  seam feature acquisition  structured light vision  
Extremely Lightweight Skeleton-Based Action Recognition With ShiftGCN plus 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2021, 卷号: 30, 页码: 7333-7348
作者:  Cheng, Ke;  Zhang, Yifan;  He, Xiangyu;  Cheng, Jian;  Lu, Hanqing
Adobe PDF(3205Kb)  |  收藏  |  浏览/下载：244/13  |  提交时间：2021/11/03
Skeleton-based action recognition  graph convolutional network  lightweight network  shift network  
Efficient and Accurate Start Point Guiding and Seam Tracking Method for Curve Weld Based on Structure Light 期刊论文
IEEE Transactions on Instrumentation and Measurement, 2021, 卷号: 70, 期号: 0, 页码: 3001310
作者:  Yunkai Ma;  Junfeng Fan;  Sai Deng;  Yu Luo;  Xihong Ma;  Fengshui Jing;  Min Tan
Adobe PDF(3660Kb)  |  收藏  |  浏览/下载：90/22  |  提交时间：2023/10/08
Distractor-aware discrimination learning for online multiple object tracking 期刊论文
PATTERN RECOGNITION, 2020, 期号: 107, 页码: 10
作者:  Zhou, Zongwei;  Luo, Wenhan;  Wang, Qiang;  Xing, Junliang;  Hu, Weiming
Adobe PDF(840Kb)  |  收藏  |  浏览/下载：358/105  |  提交时间：2020/08/31
Multi-object tracking  Distractor-aware discrimination learning  Relational attention learning  
Deep Imitation Learning for Autonomous Vehicles Based on Convolutional Neural Networks 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2020, 卷号: 7, 期号: 1, 页码: 82-95
作者:  Parham M. Kebria;  Abbas Khosravi;  Syed Moshfeq Salaken;  Saeid Nahavandi
浏览  |  Adobe PDF(7717Kb)  |  收藏  |  浏览/下载：115/31  |  提交时间：2021/03/11
Autonomous vehicles  convolutional neural networks  deep learning  imitation learning  
Robust Visual Detection and Tracking Strategies for Autonomous Aerial Refueling of UAVs 期刊论文
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2019, 卷号: 68, 期号: 12, 页码: 4640-4652
作者:  Sun, Siyang;  Yin, Yingjie;  Wang, Xingang;  Xu, De
浏览  |  Adobe PDF(11285Kb)  |  收藏  |  浏览/下载：270/56  |  提交时间：2020/03/30
Target tracking  Feature extraction  Object detection  Search problems  Proposals  Visualization  Detectors  Autonomous aerial refueling (AAR)  deep learning  object detection  object tracking  reinforcement learning