Vehicle wheel weld detection based on improved YOLO v4 algorithm

Full metadata record

DC Field	Value	Language
dc.date	2022-04
dc.date.accessioned	2025-08-27T05:21:00Z	-
dc.date.available	2025-08-27T05:21:00Z	-
dc.date.issued	2022-04
dc.identifier.identifier	Dspace\SGAU\20230217\102066
dc.identifier.citation	Liang TJ, Pan WG, Bao H, Pan F. Vehicle wheel weld detection based on improved YOLO v4 algorithm. Computer Optics 2022; 46(2): 271-279. DOI: 10.18287/2412-6179-CO-887.
dc.identifier.uri	10.18287/2412-6179-CO-887
dc.identifier.uri	http://repo.ssau.ru/jspui/handle/123456789/22888	-
dc.description.sponsorship	The work was funded by the National Natural Science Foundation of China (Nos. 61802019, 61932012, 61871039) and the Beijing Municipal Education Commission Science and Technology Program (Nos. KM201911417009, KM201911417003, KM201911417001). Beijing Union University Research and Innovation Projects for Postgraduates (No.YZ2020K001).
dc.language	en
dc.publisher	Самарский национальный исследовательский университет
dc.relation.ispartofseries	46;2
dc.title	Vehicle wheel weld detection based on improved YOLO v4 algorithm
dc.type	Article
local.identifier.olduri	http://repo.ssau.ru/handle/Zhurnal-Komputernaya-optika/Vehicle-wheel-weld-detection-based-on-improved-YOLO-v4-algorithm-102066
local.identifier.olduri	http://repo.ssau.ru/handle/Zhurnal-Komputernaya-optika/Vehicle-wheel-weld-detection-based-on-improved-YOLO-v4-algorithm-102066
Appears in Collections:	Журнал "Компьютерная оптика"

Files in This Item:

File	Description	Size	Format
13-Liang-Pan-Bao-Pan_KI-Lit-MA-SV-JuN2-Gr.pdf	Основная статья	2.23 MB	Adobe PDF	View/Open

Samara University Repository