图像多分类问题的研究

Zelin Song, Xiaoyu Wu, Jiayao Qian
{"title":"图像多分类问题的研究","authors":"Zelin Song, Xiaoyu Wu, Jiayao Qian","doi":"10.1109/ICCST53801.2021.00124","DOIUrl":null,"url":null,"abstract":"Image classification is an important research topic in the computer vision area. The classification task of small data volume, large number of classes, smaller differences between classes and larger differences within classes has always been a challenge. And this article aims to study and discuss such problems, using three methods: ResNets, EfficientNet and MoCo V2 for experiment and continuous optimization, and got the following results: The accuracy rate of ResNets classification is 0.43, of EfficientNet classification is 0.47, and of MoCo V2 classification, it is 0.62.","PeriodicalId":222463,"journal":{"name":"2021 International Conference on Culture-oriented Science & Technology (ICCST)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Research on the problem of image multi-classification\",\"authors\":\"Zelin Song, Xiaoyu Wu, Jiayao Qian\",\"doi\":\"10.1109/ICCST53801.2021.00124\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Image classification is an important research topic in the computer vision area. The classification task of small data volume, large number of classes, smaller differences between classes and larger differences within classes has always been a challenge. And this article aims to study and discuss such problems, using three methods: ResNets, EfficientNet and MoCo V2 for experiment and continuous optimization, and got the following results: The accuracy rate of ResNets classification is 0.43, of EfficientNet classification is 0.47, and of MoCo V2 classification, it is 0.62.\",\"PeriodicalId\":222463,\"journal\":{\"name\":\"2021 International Conference on Culture-oriented Science & Technology (ICCST)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference on Culture-oriented Science & Technology (ICCST)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCST53801.2021.00124\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Culture-oriented Science & Technology (ICCST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCST53801.2021.00124","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

图像分类是计算机视觉领域的一个重要研究课题。数据量小、类数多、类间差异小、类内差异大的分类任务一直是一个挑战。本文针对这些问题进行研究和讨论,采用ResNets、EfficientNet和MoCo V2三种方法进行实验和持续优化,得到如下结果:ResNets分类准确率为0.43,EfficientNet分类准确率为0.47,MoCo V2分类准确率为0.62。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on the problem of image multi-classification
Image classification is an important research topic in the computer vision area. The classification task of small data volume, large number of classes, smaller differences between classes and larger differences within classes has always been a challenge. And this article aims to study and discuss such problems, using three methods: ResNets, EfficientNet and MoCo V2 for experiment and continuous optimization, and got the following results: The accuracy rate of ResNets classification is 0.43, of EfficientNet classification is 0.47, and of MoCo V2 classification, it is 0.62.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信