{"title":"基于深度学习的课堂行为识别新方法","authors":"Ji’an You, Yaqi Huang, Shiqing Zhai, Yi Liu","doi":"10.1109/ICET55642.2022.9944414","DOIUrl":null,"url":null,"abstract":"With the rapid rise of artificial intelligence, the application of artificial intelligence in classroom teaching has become more and more extensive. Combining the related technologies of artificial intelligence with the dynamic detection of classroom behavior is a hot research topic at present. In this article, a novel recognition method of students' action in classroom is proposed. The method first uses YOLOv3 to recognize a single target in the classroom, and then, according to the proposed combination method, combines each single target into a fixed student classroom behavior. The research was carried out in eight classes (215 students in total). The research results show that the proposed research method can accurately and quickly identify students' behaviors in classroom.","PeriodicalId":169051,"journal":{"name":"2022 IEEE 2nd International Conference on Educational Technology (ICET)","volume":"111 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Deep Learning Based a Novel Method of Classroom Behavior Recognition\",\"authors\":\"Ji’an You, Yaqi Huang, Shiqing Zhai, Yi Liu\",\"doi\":\"10.1109/ICET55642.2022.9944414\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the rapid rise of artificial intelligence, the application of artificial intelligence in classroom teaching has become more and more extensive. Combining the related technologies of artificial intelligence with the dynamic detection of classroom behavior is a hot research topic at present. In this article, a novel recognition method of students' action in classroom is proposed. The method first uses YOLOv3 to recognize a single target in the classroom, and then, according to the proposed combination method, combines each single target into a fixed student classroom behavior. The research was carried out in eight classes (215 students in total). The research results show that the proposed research method can accurately and quickly identify students' behaviors in classroom.\",\"PeriodicalId\":169051,\"journal\":{\"name\":\"2022 IEEE 2nd International Conference on Educational Technology (ICET)\",\"volume\":\"111 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE 2nd International Conference on Educational Technology (ICET)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICET55642.2022.9944414\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 2nd International Conference on Educational Technology (ICET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICET55642.2022.9944414","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Deep Learning Based a Novel Method of Classroom Behavior Recognition
With the rapid rise of artificial intelligence, the application of artificial intelligence in classroom teaching has become more and more extensive. Combining the related technologies of artificial intelligence with the dynamic detection of classroom behavior is a hot research topic at present. In this article, a novel recognition method of students' action in classroom is proposed. The method first uses YOLOv3 to recognize a single target in the classroom, and then, according to the proposed combination method, combines each single target into a fixed student classroom behavior. The research was carried out in eight classes (215 students in total). The research results show that the proposed research method can accurately and quickly identify students' behaviors in classroom.