S. Watcharabutsarakham, Supphachoke Suntiwichaya, Chanchai Junlouchai, Apichon Kitvimorat
{"title":"基于CNN的单模型与多模型人脸分类比较","authors":"S. Watcharabutsarakham, Supphachoke Suntiwichaya, Chanchai Junlouchai, Apichon Kitvimorat","doi":"10.1109/iSAI-NLP51646.2020.9376825","DOIUrl":null,"url":null,"abstract":"Since the coronavirus disease 2019 (COVID-19) outbreak has spread across the country, our research applies to remind the people to wear a face mask when we go outside because a facial image detection and classification method will be used to authentication and authorization. This paper has shown that our created models based on CNN can detect the face mask-wearing, glasses-wearing, and gender with comparison two models. We training model with mix public datasets such as WIDER FACE, AFW, and MAFA. Moreover, we use VGG-Face to pre-train the model for the advance detection rate.","PeriodicalId":311014,"journal":{"name":"2020 15th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP)","volume":"276 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Comparison of Face Classification with Single and Multi-model base on CNN\",\"authors\":\"S. Watcharabutsarakham, Supphachoke Suntiwichaya, Chanchai Junlouchai, Apichon Kitvimorat\",\"doi\":\"10.1109/iSAI-NLP51646.2020.9376825\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Since the coronavirus disease 2019 (COVID-19) outbreak has spread across the country, our research applies to remind the people to wear a face mask when we go outside because a facial image detection and classification method will be used to authentication and authorization. This paper has shown that our created models based on CNN can detect the face mask-wearing, glasses-wearing, and gender with comparison two models. We training model with mix public datasets such as WIDER FACE, AFW, and MAFA. Moreover, we use VGG-Face to pre-train the model for the advance detection rate.\",\"PeriodicalId\":311014,\"journal\":{\"name\":\"2020 15th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP)\",\"volume\":\"276 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 15th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/iSAI-NLP51646.2020.9376825\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 15th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/iSAI-NLP51646.2020.9376825","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparison of Face Classification with Single and Multi-model base on CNN
Since the coronavirus disease 2019 (COVID-19) outbreak has spread across the country, our research applies to remind the people to wear a face mask when we go outside because a facial image detection and classification method will be used to authentication and authorization. This paper has shown that our created models based on CNN can detect the face mask-wearing, glasses-wearing, and gender with comparison two models. We training model with mix public datasets such as WIDER FACE, AFW, and MAFA. Moreover, we use VGG-Face to pre-train the model for the advance detection rate.