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title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð±Ð°ÐºÐ°Ð»Ð°Ð²ÑÐ°
titleType: Subtitle
title: Tuning small-sized convolutional neural networks for image classification using a genetic algorithm
Creators: name: ÐÐ¾Ð²Ð°Ð»ÐµÐ½ÐºÐ¾, Ð¡ÐµÐ¼ÑÐ½
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2022
Subjects: ÑÐ²ÐµÑÑÐ¾ÑÐ½ÑÐµ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹
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Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸
convolutional neural networks for image classification
genetic algorithmÑ
hyperparameter tuning
architecture selection
neural network training

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description: The subject of the graduate qualification work is "Tuning small-sized convolutional neural networks for image classification using a genetic algorithm". This work is carried out in order to study the application of genetic algorithms in convolutional neural networks of image classification, in particular, the application in the following areas is considered: - tuning neural network hyperparameters, - training a completely untrained network, - fine tuning neural network, - selection of model architectures.In addition, a variant of the combination of the most well-proven variants of the application of the genetic algorithm is proposed. During the implementation, the basic principles of the construction and operation of convolutional neural networks were considered, an overview of existing architectures of convolutional neural networks designed for image classification was made. The review of genetic algorithms and currently existing methods of their implementation is also carried out applicable to convolutional neural networks of image classification. As a result of the conducted tests and experiments, a conclusion was made about the most suitable directions of application of the algorithm under study in convolutional neural networks of image classification and further promising directions of their use in these networks.