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Title	Exploring Deep Learning Techniques For Vision-Based Vehicle Re-Identification: A Traffic Intersection Case Study
ID_Doc	25511
Authors	Regmi B.S.; Dailey M.N.; Ekpanyapong M.
Year	2023
Published	Communications in Computer and Information Science, 1942 CCIS
DOI	http://dx.doi.org/10.1007/978-981-99-7969-1_17
Abstract	We present a comprehensive review of recent deep learning techniques for vehicle re-identification (Re-ID) in Intelligent Transportation Systems (ITS). Vehicle Re-ID involves recognizing and matching specific vehicles across different cameras, against challenges such as pose variation, illumination, and weather. The study summarizes vision-based approaches, discusses challenges involved in real-time applications, and provides a brief comparison of methodologies and datasets available for the task. Additionally, a case study showcases an application of vehicle Re-ID at traffic junctions for the purpose of enforcing traffic rules, including identifying traffic light violations and capturing clear views of license plates for violator identification. By providing a summary of existing work and suggesting future research directions, we aim to assist researchers in advancing intelligent transportation systems and contributing to the development of smarter cities. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.
Author Keywords	ITS; Smart City; Vehicle Re-ID

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