Номер части:
ISSN: 2411-6467 (Print)
ISSN: 2413-9335 (Online)
Статьи, опубликованные в журнале, представляется читателям на условиях свободной лицензии CC BY-ND


Науки и перечень статей вошедших в журнал:
DOI: 10.31618/ESU.2413-9335.2020.4.73.677
Дата публикации статьи в журнале: 2020/05/12
Название журнала: Евразийский Союз Ученых — публикация научных статей в ежемесячном научном журнале, Выпуск: 73, Том: 4, Страницы в выпуске: 15-24
Автор: Boranbayev S.N.
, L.N.Gumilyov Eurasian National University, Nur-Sultan, Kazakhstan
Автор: Amirtayev M.S.
, L.N.Gumilyov Eurasian National University, Nur-Sultan, Kazakhstan
Анотация: The purpose of this article is to summarize the knowledge gained in the development and implementation of a neural network for facial recognition. Neural networks are used to solve complex tasks that require analytical calculations similar to what the human brain does. Machine learning algorithms are the foundation of a neural network. As input, the algorithm receives an image with people's faces, then searches for faces in this image using HOG (Histogram of oriented gradients). The result is images with explicit face structures. To determine unique facial features, the Face landmark algorithm is used, which finds 68 special points on the face. These points can be used to center the eyes and mouth for more accurate encoding. To get an accurate “face map” consisting of 128 dimensions, you need to use image encoding. Using the obtained data, the convolutional neural network can determine people's faces using the SVM linear classifier algorithm.
Ключевые слова: face recognition, method,algorithm,neural network,machine learning,deep learning,histogram,directed gradients,affine transformations,
Данные для цитирования: Boranbayev S.N. Amirtayev M.S. . DEVELOPMENT A SYSTEM FOR CLASSIFYING AND RECOGNIZING PERSON’S FACE (15-24) // Евразийский Союз Ученых — публикация научных статей в ежемесячном научном журнале. Технические науки. 2020/05/12; 73(4):15-24. 10.31618/ESU.2413-9335.2020.4.73.677

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