{"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}
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.
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