{"title":"基于多模态数据的双线性融合网络学生分心行为识别","authors":"Jian Zhang","doi":"10.4018/jcit.326131","DOIUrl":null,"url":null,"abstract":"As governments, education departments, and academic accreditation bodies have begun to encourage schools to develop evidence-based decision-making and innovation systems, learning analysis techniques have shown great advantages in decision-making aid and teaching evaluation. After integrating relevant algorithms and technologies in artificial intelligence and machine learning, learning analysis has achieved higher analysis accuracy. In order to realize the recognition of students' classroom behaviors such as standing up, sitting up, and raising hands and improve the recognition accuracy and recall rate, multi-modal data such as human key point information and RGB images are used for experiments. To further improve the feature extraction capability of the model, features are extracted from the improved ResNet-50 and EfficientNet-B0 models, and bilinear fusion is performed to further improve the recognition accuracy of the models.","PeriodicalId":43384,"journal":{"name":"Journal of Cases on Information Technology","volume":" ","pages":""},"PeriodicalIF":0.7000,"publicationDate":"2023-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Novel Bilinear Fusion Network Based on Multimodal Data for Student Distracted Behavior Recognition\",\"authors\":\"Jian Zhang\",\"doi\":\"10.4018/jcit.326131\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As governments, education departments, and academic accreditation bodies have begun to encourage schools to develop evidence-based decision-making and innovation systems, learning analysis techniques have shown great advantages in decision-making aid and teaching evaluation. After integrating relevant algorithms and technologies in artificial intelligence and machine learning, learning analysis has achieved higher analysis accuracy. In order to realize the recognition of students' classroom behaviors such as standing up, sitting up, and raising hands and improve the recognition accuracy and recall rate, multi-modal data such as human key point information and RGB images are used for experiments. To further improve the feature extraction capability of the model, features are extracted from the improved ResNet-50 and EfficientNet-B0 models, and bilinear fusion is performed to further improve the recognition accuracy of the models.\",\"PeriodicalId\":43384,\"journal\":{\"name\":\"Journal of Cases on Information Technology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2023-07-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Cases on Information Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4018/jcit.326131\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cases on Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/jcit.326131","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Novel Bilinear Fusion Network Based on Multimodal Data for Student Distracted Behavior Recognition
As governments, education departments, and academic accreditation bodies have begun to encourage schools to develop evidence-based decision-making and innovation systems, learning analysis techniques have shown great advantages in decision-making aid and teaching evaluation. After integrating relevant algorithms and technologies in artificial intelligence and machine learning, learning analysis has achieved higher analysis accuracy. In order to realize the recognition of students' classroom behaviors such as standing up, sitting up, and raising hands and improve the recognition accuracy and recall rate, multi-modal data such as human key point information and RGB images are used for experiments. To further improve the feature extraction capability of the model, features are extracted from the improved ResNet-50 and EfficientNet-B0 models, and bilinear fusion is performed to further improve the recognition accuracy of the models.
期刊介绍:
JCIT documents comprehensive, real-life cases based on individual, organizational and societal experiences related to the utilization and management of information technology. Cases published in JCIT deal with a wide variety of organizations such as businesses, government organizations, educational institutions, libraries, non-profit organizations. Additionally, cases published in JCIT report not only successful utilization of IT applications, but also failures and mismanagement of IT resources and applications.