Triangular Chain Closed-Loop Detection Network for Dense Pedestrian Detection-Reference-Cited by-同舟云学术

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Triangular Chain Closed-Loop Detection Network for Dense Pedestrian Detection

Published:2024 Issue: Volume:73 Page:1-14
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Yuan Qishen¹^ORCID,Huang Guoheng¹^ORCID,Zhong Guo²^ORCID,Yuan Xiaochen³^ORCID,Tan Zhe¹^ORCID,Lu Zeng⁴^ORCID,Pun Chi-Man⁵^ORCID

Affiliation:

1. School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China

2. School of Information Science and Technology, Guangdong University of Foreign Studies, Guangzhou, China

3. Faculty of Applied Sciences, Macau Polytechnic University, Macau, China

4. Guangzhou Quwan Network Technology Company Ltd., Guangzhou, China

5. Department of Computer and Information Science, University of Macau, Macau, China

Funder

Key Areas Research and Development Program of Guangzhou

Science and Technology Research in key areas in Foshan

Science and Technology Projects of Guangzhou

Guangdong Provincial Key Laboratory of Cyber-Physical System

Basic and Applied Basic Research Foundation of Guangdong Province

National Statistical Science Research Project of China

Science and Technology Development Fund, Macau SAR

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/10367905/10352356.pdf?arnumber=10352356

Reference65 articles.

1. MRPT : Millimeter-Wave Radar-based Pedestrian Trajectory-Tracking for Autonomous Urban Driving

2. YOLOv4-5D: An Effective and Efficient Object Detector for Autonomous Driving

3. Histograms of Oriented Gradients for Human Detection

4. Rapid object detection using a boosted cascade of simple features

5. A discriminatively trained, multiscale, deformable part model

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