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2021 | OriginalPaper | Chapter

The Study of Improving the Accuracy of Convolutional Neural Networks in Face Recognition Tasks

Authors : Nikita Andriyanov, Vitaly Dementev, Alexandr Tashlinskiy, Konstantin Vasiliev

Published in: Pattern Recognition. ICPR International Workshops and Challenges

Publisher: Springer International Publishing

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Abstract

The article discusses the efficiency of convolutional neural networks in solving the problem of face recognition of tennis players. The characteristics of training and accuracy on a test set for networks of various architectures are compared. Application of weight drop out methods and data augmentation to eliminate the effect of retraining is also considered. Finally, the transfer learning from other known networks is used. It is shown how, for initial data, it is possible to increase recognition accuracy by 25% compared to a typical convolutional neural network.

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Title: The Study of Improving the Accuracy of Convolutional Neural Networks in Face Recognition Tasks
Authors: Nikita Andriyanov
Vitaly Dementev
Alexandr Tashlinskiy
Konstantin Vasiliev
Publisher: Springer International Publishing
Book: Pattern Recognition. ICPR International Workshops and Challenges
Print ISBN: 978-3-030-68820-2

Electronic ISBN: 978-3-030-68821-9

Copyright Year: 2021
DOI: https://doi.org/10.1007/978-3-030-68821-9_1

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