{"title":"YOLO目标检测算法概述","authors":"Chengjuan Wan, Yuxuan Pang, Shanzhen Lan","doi":"10.56028/ijcit.1.2.11","DOIUrl":null,"url":null,"abstract":"As an important research direction in the field of computer vision, object detection has developed \nrapidly and many kinds of mature algorithms emerged. The series of YOLO (You Only Look Once) \nalgorithms implement one-stage detection based on regression ideas, which showing preeminent \nin speed and owning strong generalization on a variety of datasets. This paper will give a simple \nintroduction to the current mainstream deep learning object detection algorithm, then focus on \ncombing the principle and optimizational process of the series of YOLO algorithms, summarize \nthe latest \nbreakthroughs in YOLO algorithm, Hopefully that can provide reference for the \nresearch of related topics.","PeriodicalId":393159,"journal":{"name":"International Journal of Computing and Information Technology","volume":"401 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Overview of YOLO Object Detection Algorithm\",\"authors\":\"Chengjuan Wan, Yuxuan Pang, Shanzhen Lan\",\"doi\":\"10.56028/ijcit.1.2.11\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As an important research direction in the field of computer vision, object detection has developed \\nrapidly and many kinds of mature algorithms emerged. The series of YOLO (You Only Look Once) \\nalgorithms implement one-stage detection based on regression ideas, which showing preeminent \\nin speed and owning strong generalization on a variety of datasets. This paper will give a simple \\nintroduction to the current mainstream deep learning object detection algorithm, then focus on \\ncombing the principle and optimizational process of the series of YOLO algorithms, summarize \\nthe latest \\nbreakthroughs in YOLO algorithm, Hopefully that can provide reference for the \\nresearch of related topics.\",\"PeriodicalId\":393159,\"journal\":{\"name\":\"International Journal of Computing and Information Technology\",\"volume\":\"401 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-08-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Computing and Information Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.56028/ijcit.1.2.11\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computing and Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.56028/ijcit.1.2.11","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
摘要
目标检测作为计算机视觉领域的一个重要研究方向,发展迅速,出现了多种成熟的算法。YOLO (You Only Look Once)算法系列实现了基于回归思想的单阶段检测,在速度上具有优势,并且在各种数据集上具有很强的泛化能力。本文将对当前主流的深度学习目标检测算法进行简单介绍,然后重点梳理YOLO算法系列的原理和优化过程,总结YOLO算法的最新突破,希望能为相关课题的研究提供参考。
As an important research direction in the field of computer vision, object detection has developed
rapidly and many kinds of mature algorithms emerged. The series of YOLO (You Only Look Once)
algorithms implement one-stage detection based on regression ideas, which showing preeminent
in speed and owning strong generalization on a variety of datasets. This paper will give a simple
introduction to the current mainstream deep learning object detection algorithm, then focus on
combing the principle and optimizational process of the series of YOLO algorithms, summarize
the latest
breakthroughs in YOLO algorithm, Hopefully that can provide reference for the
research of related topics.