Autors: Ismailov, A. V., Hristov, V. D.
Title: YOLO Performance Comparison on Stock Images of Grocery Products
Keywords: classification, grocery products, stock images, YOLO

Abstract: This paper compares the classification performance of the YOLO models in the cases where the input data is limited or purely generated from stock images. For this purpose, YOLOv5n, YOLOv5s, YOLOv8n, and YOLOv8s were trained to classify stock images into 219 categories of grocery products.

References

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Issue

National Conference with International Participation, TELECOM, 2025, Bulgaria, https://doi.org/10.1109/TELECOM63374.2024.10812185

Цитирания (Citation/s):
1. Deng H., Liang P., Liao Z., Yuan J., Wu H., CAE-YOLOv11n: Research on Commodity Classification for Retail Automated Checkout Systems, 2025, 2025 5th International Conference on Computer Vision Application and Algorithm Cvaa 2025, issue 0, pp. 457-462, DOI 10.1109/CVAA66438.2025.11193397 - 2025 - в издания, индексирани в Scopus

Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus