{"title":"用于大学学位验证的人脸图像自动分析","authors":"Ruslan Zulkashev, M. Polyak","doi":"10.1109/ITNT57377.2023.10139216","DOIUrl":null,"url":null,"abstract":"The article discusses application of machine learning to physiognomy. Two different neural-network models are examined as feature extractors from face images. In total three classifiers are trained and compared with each other, pursuing the goal of answering a question if it is possible to automatically verify a college degree based only on a human face. Our findings show that to a certain extent it is possible.","PeriodicalId":296438,"journal":{"name":"2023 IX International Conference on Information Technology and Nanotechnology (ITNT)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Automatic analysis of face images for college degree verification\",\"authors\":\"Ruslan Zulkashev, M. Polyak\",\"doi\":\"10.1109/ITNT57377.2023.10139216\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The article discusses application of machine learning to physiognomy. Two different neural-network models are examined as feature extractors from face images. In total three classifiers are trained and compared with each other, pursuing the goal of answering a question if it is possible to automatically verify a college degree based only on a human face. Our findings show that to a certain extent it is possible.\",\"PeriodicalId\":296438,\"journal\":{\"name\":\"2023 IX International Conference on Information Technology and Nanotechnology (ITNT)\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-04-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IX International Conference on Information Technology and Nanotechnology (ITNT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITNT57377.2023.10139216\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IX International Conference on Information Technology and Nanotechnology (ITNT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITNT57377.2023.10139216","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automatic analysis of face images for college degree verification
The article discusses application of machine learning to physiognomy. Two different neural-network models are examined as feature extractors from face images. In total three classifiers are trained and compared with each other, pursuing the goal of answering a question if it is possible to automatically verify a college degree based only on a human face. Our findings show that to a certain extent it is possible.
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