P. G. K. Prince, J. J. Bethanney, S. Poojahsri, S.K Sounder, J. Premalatha, D. Marshiana
{"title":"使用非接触宽度分析仪识别情绪","authors":"P. G. K. Prince, J. J. Bethanney, S. Poojahsri, S.K Sounder, J. Premalatha, D. Marshiana","doi":"10.1109/ICCPC55978.2022.10072117","DOIUrl":null,"url":null,"abstract":"Automation of emotion detection has been done in many methods. The method followed here is detection of emotions through the pattern of respiration. A non-contact infrared temperature sensor is used to detect the pattern of respiration. The signals acquired from the sensor in analyzed. 10 statistical features are extracted. Feature reduction is done by applying Principle component analysis and 4 PCAs are obtained. These features are applied to supervised and unsupervised classification algorithm. Trilayered neural network has an accuracy of 95.5%","PeriodicalId":367848,"journal":{"name":"2022 International Conference on Computer, Power and Communications (ICCPC)","volume":"144 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Recognition of emotions using non-contact breadth analyzer\",\"authors\":\"P. G. K. Prince, J. J. Bethanney, S. Poojahsri, S.K Sounder, J. Premalatha, D. Marshiana\",\"doi\":\"10.1109/ICCPC55978.2022.10072117\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Automation of emotion detection has been done in many methods. The method followed here is detection of emotions through the pattern of respiration. A non-contact infrared temperature sensor is used to detect the pattern of respiration. The signals acquired from the sensor in analyzed. 10 statistical features are extracted. Feature reduction is done by applying Principle component analysis and 4 PCAs are obtained. These features are applied to supervised and unsupervised classification algorithm. Trilayered neural network has an accuracy of 95.5%\",\"PeriodicalId\":367848,\"journal\":{\"name\":\"2022 International Conference on Computer, Power and Communications (ICCPC)\",\"volume\":\"144 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Conference on Computer, Power and Communications (ICCPC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCPC55978.2022.10072117\",\"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 International Conference on Computer, Power and Communications (ICCPC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCPC55978.2022.10072117","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Recognition of emotions using non-contact breadth analyzer
Automation of emotion detection has been done in many methods. The method followed here is detection of emotions through the pattern of respiration. A non-contact infrared temperature sensor is used to detect the pattern of respiration. The signals acquired from the sensor in analyzed. 10 statistical features are extracted. Feature reduction is done by applying Principle component analysis and 4 PCAs are obtained. These features are applied to supervised and unsupervised classification algorithm. Trilayered neural network has an accuracy of 95.5%
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