{"title":"人脸识别与定位的反向传播网络","authors":"G. Sarker","doi":"10.1109/ReTIS.2011.6146834","DOIUrl":null,"url":null,"abstract":"The entire process of face detection, identification and localization of faces should preferably be almost orientation or rotation invariant. The present paper aims to design one optimal Back Propagation (BP) Network model to perform these face identification tasks. The task is partially independent of orientation or rotation of the faces in the image. Also the identification rate of the faces is quiet moderate.","PeriodicalId":137916,"journal":{"name":"2011 International Conference on Recent Trends in Information Systems","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"A Back Propagation Network for face identification and localization\",\"authors\":\"G. Sarker\",\"doi\":\"10.1109/ReTIS.2011.6146834\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The entire process of face detection, identification and localization of faces should preferably be almost orientation or rotation invariant. The present paper aims to design one optimal Back Propagation (BP) Network model to perform these face identification tasks. The task is partially independent of orientation or rotation of the faces in the image. Also the identification rate of the faces is quiet moderate.\",\"PeriodicalId\":137916,\"journal\":{\"name\":\"2011 International Conference on Recent Trends in Information Systems\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 International Conference on Recent Trends in Information Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ReTIS.2011.6146834\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on Recent Trends in Information Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ReTIS.2011.6146834","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Back Propagation Network for face identification and localization
The entire process of face detection, identification and localization of faces should preferably be almost orientation or rotation invariant. The present paper aims to design one optimal Back Propagation (BP) Network model to perform these face identification tasks. The task is partially independent of orientation or rotation of the faces in the image. Also the identification rate of the faces is quiet moderate.