A comparative study of YOLOv5 models performance for image localization and classification (CROSBI ID 723483)
Prilog sa skupa u časopisu | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Horvat, Marko ; Jelečević, Ljudevit ; Gledec, Gordan
engleski
A comparative study of YOLOv5 models performance for image localization and classification
YOLOv5 is one of the latest and often used versions of a very popular deep learning neural network used for various machine learning tasks, mainly in computer vision. The YOLO algorithm has steadily gained acceptance in the data science community due to its superior performance in complex and noisy data environments, availability, and ease of use in combination with widely used programming languages such as Python. This paper aims to compare different versions of the YOLOv5 model using an everyday image dataset and to provide researchers with precise suggestions for selecting the optimal model for a given problem type. The obtained results and the implemented YOLOv5 models are available for non-commercial use at: https://github.com/mhorvat/YOLOv5-models-comparison
computer vision, image classification, deep learning, deep convolutional neural networks, YOLO
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Podaci o prilogu
349-356.
2022.
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objavljeno
Podaci o matičnoj publikaciji
Central European conference on information and intelligent systems
Vrček, Neven ; Guàrdia, Lourdes ; Grd, Petra
Varaždin: Fakultet organizacije i informatike Sveučilišta u Zagrebu
1847-2001
1848-2295
Podaci o skupu
33rd Central European Conference on Information and Intelligent Systems (CECIIS 2022)
predavanje
21.09.2022-23.09.2022
Dubrovnik, Hrvatska