VehicleNet: Learning Robust Visual Representation for Vehicle Re-Identification

10.1109/TMM.2020.3014488

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Bibliographic Details
Main Authors:	Zheng, Zhedong, Ruan, Tao, Wei, Yunchao, Yang, Yi, Mei, Tao
Other Authors:	DEPARTMENT OF COMPUTER SCIENCE
Format:	Article
Language:	English
Published:	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC 2023
Subjects:	Science & Technology Technology Computer Science, Information Systems Computer Science, Software Engineering Telecommunications Computer Science Training Robustness Adaptation models Data models Automobiles Cameras Feature extraction Vehicle re-identification image representation convolutional neural networks PERSON REIDENTIFICATION
Online Access:	https://scholarbank.nus.edu.sg/handle/10635/245916
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Institution:	National University of Singapore
Language:	English

id	sg-nus-scholar.10635-245916
record_format	dspace
spelling	sg-nus-scholar.10635-2459162024-04-17T09:01:22Z VehicleNet: Learning Robust Visual Representation for Vehicle Re-Identification Zheng, Zhedong Ruan, Tao Wei, Yunchao Yang, Yi Mei, Tao DEPARTMENT OF COMPUTER SCIENCE ELECTRICAL AND COMPUTER ENGINEERING Science & Technology Technology Computer Science, Information Systems Computer Science, Software Engineering Telecommunications Computer Science Training Robustness Adaptation models Data models Automobiles Cameras Feature extraction Vehicle re-identification image representation convolutional neural networks PERSON REIDENTIFICATION 10.1109/TMM.2020.3014488 IEEE TRANSACTIONS ON MULTIMEDIA 23 2683-2693 2023-11-14T03:00:43Z 2023-11-14T03:00:43Z 2021 2023-11-10T11:43:23Z Article Zheng, Zhedong, Ruan, Tao, Wei, Yunchao, Yang, Yi, Mei, Tao (2021). VehicleNet: Learning Robust Visual Representation for Vehicle Re-Identification. IEEE TRANSACTIONS ON MULTIMEDIA 23 : 2683-2693. ScholarBank@NUS Repository. https://doi.org/10.1109/TMM.2020.3014488 1520-9210 1941-0077 https://scholarbank.nus.edu.sg/handle/10635/245916 en IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC Elements
institution	National University of Singapore
building	NUS Library
continent	Asia
country	Singapore Singapore
content_provider	NUS Library
collection	ScholarBank@NUS
language	English
topic	Science & Technology Technology Computer Science, Information Systems Computer Science, Software Engineering Telecommunications Computer Science Training Robustness Adaptation models Data models Automobiles Cameras Feature extraction Vehicle re-identification image representation convolutional neural networks PERSON REIDENTIFICATION
spellingShingle	Science & Technology Technology Computer Science, Information Systems Computer Science, Software Engineering Telecommunications Computer Science Training Robustness Adaptation models Data models Automobiles Cameras Feature extraction Vehicle re-identification image representation convolutional neural networks PERSON REIDENTIFICATION Zheng, Zhedong Ruan, Tao Wei, Yunchao Yang, Yi Mei, Tao VehicleNet: Learning Robust Visual Representation for Vehicle Re-Identification
description	10.1109/TMM.2020.3014488
author2	DEPARTMENT OF COMPUTER SCIENCE
author_facet	DEPARTMENT OF COMPUTER SCIENCE Zheng, Zhedong Ruan, Tao Wei, Yunchao Yang, Yi Mei, Tao
format	Article
author	Zheng, Zhedong Ruan, Tao Wei, Yunchao Yang, Yi Mei, Tao
author_sort	Zheng, Zhedong
title	VehicleNet: Learning Robust Visual Representation for Vehicle Re-Identification
title_short	VehicleNet: Learning Robust Visual Representation for Vehicle Re-Identification
title_full	VehicleNet: Learning Robust Visual Representation for Vehicle Re-Identification
title_fullStr	VehicleNet: Learning Robust Visual Representation for Vehicle Re-Identification
title_full_unstemmed	VehicleNet: Learning Robust Visual Representation for Vehicle Re-Identification
title_sort	vehiclenet: learning robust visual representation for vehicle re-identification
publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
publishDate	2023
url	https://scholarbank.nus.edu.sg/handle/10635/245916
_version_	1800915979339825152

VehicleNet: Learning Robust Visual Representation for Vehicle Re-Identification

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