A Review of Yolo Algorithm Developments

Peiyuan Jiang, Daji Ergu*, Fangyao Liu, Ying Cai, Bo Ma

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

936 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)1066-1073
Number of pages8
JournalProcedia Computer Science
Volume199
DOIs
Publication statusPublished - 2021
Externally publishedYes
Event8th International Conference on Information Technology and Quantitative Management, ITQM 2020 and 2021 - Chengdu, China
Duration: 9 Jul 202111 Jul 2021

Keywords

  • Object detection
  • Public data analysis
  • Review
  • Yolo

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