{"title":"深度学习在识别学生学习情绪中的应用与优化","authors":"Zheng Wu, Dandan Pan","doi":"10.18280/ts.410133","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":49430,"journal":{"name":"Traitement Du Signal","volume":null,"pages":null},"PeriodicalIF":1.2000,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Application and Optimization of Deep Learning in Recognizing Student Learning Emotions\",\"authors\":\"Zheng Wu, Dandan Pan\",\"doi\":\"10.18280/ts.410133\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\",\"PeriodicalId\":49430,\"journal\":{\"name\":\"Traitement Du Signal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2024-02-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Traitement Du Signal\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.18280/ts.410133\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Traitement Du Signal","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.18280/ts.410133","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
期刊介绍:
The TS provides rapid dissemination of original research in the field of signal processing, imaging and visioning. Since its founding in 1984, the journal has published articles that present original research results of a fundamental, methodological or applied nature. The editorial board welcomes articles on the latest and most promising results of academic research, including both theoretical results and case studies.
The TS welcomes original research papers, technical notes and review articles on various disciplines, including but not limited to:
Signal processing
Imaging
Visioning
Control
Filtering
Compression
Data transmission
Noise reduction
Deconvolution
Prediction
Identification
Classification.