Object Detection Using AutoML and YOLO: A Comparative Analysis of EasyDL, YOLOv8, and YOLOv10

Chen, Jiaxiang (2025) Object Detection Using AutoML and YOLO: A Comparative Analysis of EasyDL, YOLOv8, and YOLOv10. In: Proceedings of the 2nd International Conference on Machine Learning and Automation, CONF-MLA 2024, November 21, 2024, Adana, Turkey.

[thumbnail of 71859.pdf] PDF
71859.pdf

Download (1MB)

Abstract

Object detection technology has been applied in multiple fields, and compared to traditional methods, using AutoML to complete object detection tasks may be more convenient and less labor-intensive. This study focuses on the performance of object detection models, comparing the AutoML platform EasyD

Item Type: Conference or Workshop Item (UNSPECIFIED)
Date Deposited: 04 Mar 2026 18:27
Last Modified: 16 Apr 2026 21:38
URI: http://eprints.eai.eu/id/eprint/52539

Actions (login required)

View Item
View Item