{"title":"利用面部特征检测脑卒中症状的研究","authors":"Sabina Umirzakova, T. Whangbo","doi":"10.1109/ICTC.2018.8539440","DOIUrl":null,"url":null,"abstract":"This paper present the early symptoms of stroke detection using face features. To achieve that, in this paper calculated wrinkles on forehead area, eye moving, mouth drooping, cheek line detection. Experimental results show that proposed stroke detection method achieved good results in this field.","PeriodicalId":417962,"journal":{"name":"2018 International Conference on Information and Communication Technology Convergence (ICTC)","volume":"162 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"STUDY ON DETECT STROKE SYMPTOMS USING FACE FEATURES\",\"authors\":\"Sabina Umirzakova, T. Whangbo\",\"doi\":\"10.1109/ICTC.2018.8539440\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper present the early symptoms of stroke detection using face features. To achieve that, in this paper calculated wrinkles on forehead area, eye moving, mouth drooping, cheek line detection. Experimental results show that proposed stroke detection method achieved good results in this field.\",\"PeriodicalId\":417962,\"journal\":{\"name\":\"2018 International Conference on Information and Communication Technology Convergence (ICTC)\",\"volume\":\"162 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on Information and Communication Technology Convergence (ICTC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICTC.2018.8539440\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Information and Communication Technology Convergence (ICTC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICTC.2018.8539440","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
STUDY ON DETECT STROKE SYMPTOMS USING FACE FEATURES
This paper present the early symptoms of stroke detection using face features. To achieve that, in this paper calculated wrinkles on forehead area, eye moving, mouth drooping, cheek line detection. Experimental results show that proposed stroke detection method achieved good results in this field.