Comparative Analysis of YOLO Variants Based on Performance Evaluation for Object Detection
This study focuses on analysing and exploring the You Only Look Once (YOLO) algorithm. Specifically, this article analyses the evolution and performance of three versions (YOLOv1, YOLOv5, and YOLOv8) in object detection. The research begins by detailing the fundamental concepts of object detection a...
Saved in:
Main Author: | Chen Aoxiang |
---|---|
Format: | Article |
Language: | English |
Published: |
EDP Sciences
2025-01-01
|
Series: | ITM Web of Conferences |
Online Access: | https://www.itm-conferences.org/articles/itmconf/pdf/2025/01/itmconf_dai2024_03008.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Enhancing surface detection: A comprehensive analysis of various YOLO models
by: G. Deepti Raj, et al.
Published: (2025-02-01) -
DFTD-YOLO: Lightweight Multi-Target Detection From Unmanned Aerial Vehicle Viewpoints
by: Yuteng Chen, et al.
Published: (2025-01-01) -
Fusion of multi-scale attention for aerial images small-target detection model based on PARE-YOLO
by: Huiying Zhang, et al.
Published: (2025-02-01) -
Light-YOLO: a lightweight detection algorithm based on multi-scale feature enhancement for infrared small ship target
by: Ji Tang, et al.
Published: (2025-01-01) -
Comparisons of performances of structural variants detection algorithms in solitary or combination strategy.
by: De-Min Duan, et al.
Published: (2025-01-01)