Журнал «Информационные технологии и вычислительные системы» - А. В. Осипов, А. Е. Сапожников, Е. С. Плешакова, С. Т. Гатауллин "Методы машинного обучения для распознавания эмоционального состояния абонента телекоммуникационных систем"

Просматривается номер 2024 / 01

В статье описывается модификация капсульной нейросети, использующая оконное преобразование Фурье (WFT)-2D-CapsNet, которая позволила по графику фотоплетизмограммы (ФПГ) с точностью 82% выявить состояние паники-ступора, не позволяющее человеку принимать логически обоснованные решения. При синхронизации смарт-браслета со смартфоном метод позволяет в режиме реального времени отслеживать подобные состояния, что позволяет реагировать на звонок телефонного мошенника при разговоре с абонентом.

Ключевые слова:

робототехника, искусственный интеллект, нейронные сети, инженерия, CapsNet, смарт-браслет, фотоплетизмограмма, эмоциональное состояние.

DOI 10.14357/20718632240103

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