The Neural Network Models Effectiveness for Face Detection and Face Recognition

Autor:	Oleksandr Bohomolov, Kirill Smelyakov, Anastasiya Chupryna, Nikita Hunko
Rok vydání:	2021
Předmět:	ComputingMethodologies_PATTERNRECOGNITION Artificial neural network business.industry Computer science Measurement uncertainty Pattern recognition Artificial intelligence business Face detection Facial recognition system Convolutional neural network
Zdroj:	2021 IEEE Open Conference of Electrical, Electronic and Information Sciences (eStream).
DOI:	10.1109/estream53087.2021.9431476
Popis:	The paper is devoted to estimation of the effectiveness of the use of modern convolutional neural networks for face detection and face recognition. On standard and custom datasets, learning of neural networks and comparison of the effectiveness of their functioning are carried out. An algorithm and recommendations are proposed regarding the practical application of the neural networks for detecting faces on digital photographs.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::a8eb3ebed5d74c98b83ee4db0c7452f1 https://doi.org/10.1109/estream53087.2021.9431476 Zobrazit plný text záznamu