{"title":"不同环境影响条件下的人脸识别效率","authors":"V. Baliar, Roman Fokin, O. Mazurkiewicz","doi":"10.1109/PICST54195.2021.9772120","DOIUrl":null,"url":null,"abstract":"his article concentrated on the study of modern deep learning algorithms for face recognition, to determine methods for as-sessing the effectiveness of detection. On the basis of the most optimal in terms of hardware algorithm implementation to de-termine the impact of capturing conditions on the resulting characteristics of the algorithm with establishing the most opti-mal conditions for its usage in real environment. For major task of the study the hardware complex was implemented based on typical IP camera and specialized computer. The obtained re-sults can be used during implementation of such systems in CCTV applications and improving deep learning face recognition algorithms during scientific studies.","PeriodicalId":391592,"journal":{"name":"2021 IEEE 8th International Conference on Problems of Infocommunications, Science and Technology (PIC S&T)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Face Recognition Efficiency for Different Environmental Influence Conditions\",\"authors\":\"V. Baliar, Roman Fokin, O. Mazurkiewicz\",\"doi\":\"10.1109/PICST54195.2021.9772120\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"his article concentrated on the study of modern deep learning algorithms for face recognition, to determine methods for as-sessing the effectiveness of detection. On the basis of the most optimal in terms of hardware algorithm implementation to de-termine the impact of capturing conditions on the resulting characteristics of the algorithm with establishing the most opti-mal conditions for its usage in real environment. For major task of the study the hardware complex was implemented based on typical IP camera and specialized computer. The obtained re-sults can be used during implementation of such systems in CCTV applications and improving deep learning face recognition algorithms during scientific studies.\",\"PeriodicalId\":391592,\"journal\":{\"name\":\"2021 IEEE 8th International Conference on Problems of Infocommunications, Science and Technology (PIC S&T)\",\"volume\":\"43 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-10-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 8th International Conference on Problems of Infocommunications, Science and Technology (PIC S&T)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PICST54195.2021.9772120\",\"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 IEEE 8th International Conference on Problems of Infocommunications, Science and Technology (PIC S&T)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PICST54195.2021.9772120","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Face Recognition Efficiency for Different Environmental Influence Conditions
his article concentrated on the study of modern deep learning algorithms for face recognition, to determine methods for as-sessing the effectiveness of detection. On the basis of the most optimal in terms of hardware algorithm implementation to de-termine the impact of capturing conditions on the resulting characteristics of the algorithm with establishing the most opti-mal conditions for its usage in real environment. For major task of the study the hardware complex was implemented based on typical IP camera and specialized computer. The obtained re-sults can be used during implementation of such systems in CCTV applications and improving deep learning face recognition algorithms during scientific studies.