A Review of Yolo Algorithm Developments

Object detection techniques are the foundation for the artificial intelligence field. This research paper gives a brief overview of the You Only Look Once (YOLO) algorithm and its subsequent advanced versions. Through the analysis, we reach many remarks and insightful results. The results show the d...

Full description

Saved in:
Bibliographic Details
Main Authors: Jiang, Peiyuan, Ergu, Daji, Liu, Fangyao, Cai, Ying, Ma, Bo
Format: Conference Proceeding
Language:English
Subjects:
Object Detection
Public Data Analysis
Review
Yolo
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Object detection techniques are the foundation for the artificial intelligence field. This research paper gives a brief overview of the You Only Look Once (YOLO) algorithm and its subsequent advanced versions. Through the analysis, we reach many remarks and insightful results. The results show the differences and similarities among the YOLO versions and between YOLO and Convolutional Neural Networks (CNNs). The central insight is the YOLO algorithm improvement is still ongoing.This article briefly describes the development process of the YOLO algorithm, summarizes the methods of target recognition and feature selection, and provides literature support for the targeted picture news and feature extraction in the financial and other fields. Besides, this paper contributes a lot to YOLO and other object detection literature.
ISSN:1877-0509
1877-0509
DOI:10.1016/j.procs.2022.01.135