Please use this identifier to cite or link to this item: http://earchive.tpu.ru/handle/11683/58182
Title: Исследование сверточной нейронной сети небольшой архитектуры для распознавания жестов
Other Titles: Small architecture convolutional neural network study for gesture recognition
Authors: Мамонова, Татьяна Егоровна
Булыгин, Д. А.
Keywords: сверточные сети; сверточные нейронные сети; распознавание жестов; компьютерное зрение; искусственный интеллект; архитектура; точность
Issue Date: 2019
Citation: Мамонова Т. Е. Исследование сверточной нейронной сети небольшой архитектуры для распознавания жестов / Т. Е. Мамонова, Д. А. Булыгин // Современные технологии, экономика и образование : сборник трудов Всероссийской научно-методической конференции, г. Томск, 27-29 декабря 2019 г. — Томск : Изд-во ТПУ, 2019. — [С. 157-159].
Abstract: Currently, more research is aimed at solving problems using computer vision and artificial intelligence. Most frequent are solutions and approaches using gesture recognition based on infrared sensors or neural networks. The relevance of the subject matter is due to the possibility of applying the proposed approach for managing the operation of objects without tactile contact and voice identification of commands, as well as its simplicity from the point of view of the end-user. This paper proposes a proprietary convolutional neural network architecture to solve gesture classification. The accuracy of the network operation was evaluated depending on the distance between the camera and the hand, as well as depending on the complexity of the gesture.
URI: http://earchive.tpu.ru/handle/11683/58182
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