Object Detection in Autonomous Vehicles under Adverse Weather: A Review of Traditional and Deep Learning Approaches

Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/42579

Title:	Object Detection in Autonomous Vehicles under Adverse Weather: A Review of Traditional and Deep Learning Approaches
Authors:	Tahir, Noor Ul Ain Zhang, Zuping Asim, Muhammad CHEN, Junhong ELAffendi, Mohammed
Issue Date:	2024
Publisher:	MDPI
Source:	Algorithms, 17 (3) (Art N° 103)
Notes:	Zhang, ZP (corresponding author), Cent South Univ, Sch Comp Sci & Engn, Changsha 410083, Peoples R China.; Asim, M (corresponding author), Prince Sultan Univ, Coll Comp & Informat Sci, EIAS Data Sci & Blockchain Lab, Riyadh 11586, Saudi Arabia.; Asim, M (corresponding author), Guangdong Univ Technol, Sch Comp Sci & Technol, Guangzhou 510006, Peoples R China. 214718021@csu.edu.cn; zpzhang@csu.edu.cn; asimpk@gdut.edu.cn; junhong.chen@uhasselt.be; affendi@psu.edu.sa
Other:	A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Algorithms for Multidisciplinary Applications".
Keywords:	intelligent transportation system;autonomous vehicles;object detection;deep learning;traditional approaches
Document URI:	http://hdl.handle.net/1942/42579
e-ISSN:	1999-4893
DOI:	10.3390/a17030103
ISI #:	001191814000001
Rights:	2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Category:	A1
Type:	Journal Contribution
Appears in Collections:	Research publications

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