{"title":"基于卷积神经网络的面部表情识别优化研究","authors":"Zirui Leng","doi":"10.1109/CONF-SPML54095.2021.00066","DOIUrl":null,"url":null,"abstract":"With the development of deep learning in recent years, artificial intelligence has been widely applied in daily lives, industries, and services, which has attracted widespread attention. Based on the above application, this paper studies the typical application technology of artificial intelligence, and builds an “emotional intelligence” model using traditional facial emotion recognition as an example, accelerating the response of the model as much as possible while ensuring correct recognition.","PeriodicalId":415094,"journal":{"name":"2021 International Conference on Signal Processing and Machine Learning (CONF-SPML)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Research on Optimizing Facial Expression Recognition Based on Convolutional Neural Network\",\"authors\":\"Zirui Leng\",\"doi\":\"10.1109/CONF-SPML54095.2021.00066\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the development of deep learning in recent years, artificial intelligence has been widely applied in daily lives, industries, and services, which has attracted widespread attention. Based on the above application, this paper studies the typical application technology of artificial intelligence, and builds an “emotional intelligence” model using traditional facial emotion recognition as an example, accelerating the response of the model as much as possible while ensuring correct recognition.\",\"PeriodicalId\":415094,\"journal\":{\"name\":\"2021 International Conference on Signal Processing and Machine Learning (CONF-SPML)\",\"volume\":\"33 1\",\"pages\":\"0\"},\"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 Signal Processing and Machine Learning (CONF-SPML)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CONF-SPML54095.2021.00066\",\"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 Signal Processing and Machine Learning (CONF-SPML)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CONF-SPML54095.2021.00066","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Optimizing Facial Expression Recognition Based on Convolutional Neural Network
With the development of deep learning in recent years, artificial intelligence has been widely applied in daily lives, industries, and services, which has attracted widespread attention. Based on the above application, this paper studies the typical application technology of artificial intelligence, and builds an “emotional intelligence” model using traditional facial emotion recognition as an example, accelerating the response of the model as much as possible while ensuring correct recognition.