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A Weakly-Supervised Crowd Density Estimation Method Based on Two-Stage Linear Feature Calibration 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 4, 页码: 965-981
作者:  Yong-Chao Li;  Rui-Sheng Jia;  Ying-Xiang Hu;  Hong-Mei Sun
Adobe PDF(10448Kb)  |  收藏  |  浏览/下载：53/25  |  提交时间：2024/03/18
Crowd density estimation  linear feature calibration  vision transformer  weakly-supervision learning  
Automatic Lane-Level Intersection Map Generation using Low-Channel Roadside LiDAR 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 5, 页码: 1209-1222
作者:  Hui Liu;  Ciyun Lin;  Bowen Gong;  Dayong Wu
Adobe PDF(16514Kb)  |  收藏  |  浏览/下载：148/37  |  提交时间：2023/04/26
High-definition map  lane-level intersection map  roadside LiDAR  sliding window  traffic object trajectory  
Multi-Source Adaptive Selection and Fusion for Pedestrian Dead Reckoning 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2022, 卷号: 9, 期号: 12, 页码: 2174-2185
作者:  Yuanxun Zheng;  Qinghua Li;  Changhong Wang;  Xiaoguang Wang;  Lifeng Hu
Adobe PDF(7050Kb)  |  收藏  |  浏览/下载：171/59  |  提交时间：2022/12/02
Adaptive reliability evaluation  adaptive weight evaluation  Kalman filter (KF)  multi-source fusion  optimal set selection  
Towards Collaborative Robotics in Top View Surveillance: A Framework for Multiple Object Tracking by Detection Using Deep Learning 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2021, 卷号: 8, 期号: 7, 页码: 1253-1270
作者:  Imran Ahmed;  Sadia Din;  Gwanggil Jeon;  Francesco Piccialli;  Giancarlo Fortino
Adobe PDF(69436Kb)  |  收藏  |  浏览/下载：159/17  |  提交时间：2021/06/11
Collaborative robotics  deep learning  object detection and tracking  top view  video surveillance  
Learning Deep RGBT Representations for Robust Person Re-identification 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 3, 页码: 443-456
作者:  Ai-Hua Zheng;  Zi-Han Chen;  Cheng-Long Li;  Jin Tang;  Bin Luo
Adobe PDF(1832Kb)  |  收藏  |  浏览/下载：278/59  |  提交时间：2021/05/24
Person re-identification (Re-ID)  thermal infrared  generative networks  attention  deep learning  
A Survey of the Research Status of Pedestrian Dead Reckoning Systems Based on Inertial Sensors 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 1, 页码: 65-83
作者:  Yuan Wu;  Hai-Bing Zhu;  Qing-Xiu Du;  Shu-Ming Tang
Adobe PDF(1248Kb)  |  收藏  |  浏览/下载：268/81  |  提交时间：2021/02/22
Inertial measurement unit (IMU)  pedestrian dead-reckoning  indoor navigation  technical route  general framework.