An Efficient Multi-Object Tracking Guided by Spatial Clustering on Vision Sensors-Reference-Cited by-同舟云学术

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An Efficient Multi-Object Tracking Guided by Spatial Clustering on Vision Sensors

Published:2024-06-15 Issue:12 Volume:24 Page:19344-19351
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Chen Yulin¹^ORCID,Li Zongtan²,Wu Linhuang³^ORCID,Chen Pingping¹^ORCID

Affiliation:

1. Department of Electronic Information, Fuzhou University, Fuzhou, China

2. Department of Electrical and Computer Engineering, College of Engineering, University of Georgia, Athens, GA, USA

3. Department of Communication Engineering, Fuzhou University, Fuzhou, China

Funder

National Natural Science Foundation of China

Fujian Distinguished Talent Project

Fujian Province Key Technique Project

Fuzhou Science and technology planning Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7361/10558706/10508744.pdf?arnumber=10508744

Reference44 articles.

1. Track to Detect and Segment: An Online Multi-Object Tracker

2. Dual Teacher: A Semisupervised Cotraining Framework for Cross-Domain Ship Detection

3. Visible-Infrared Person Re-Identification via Partially Interactive Collaboration

4. Multi-Feature Fusion in Particle Filter Framework for Visual Tracking

5. Self-Supervised Deep Correlation Tracking

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. YOLOv5 Integrated With Recurrent Network for Object Tracking: Experimental Results From a Hardware Platform;IEEE Access;2024

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