An Approach to Using MobileNet CNN-model for Gesture Recognition

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dc.contributor.authorMazurets, O.
dc.contributor.authorZalutska, O.
dc.contributor.authorTyschenko, O.
dc.contributor.authorBohdanova, A.
dc.contributor.authorМазурець, Олександр Вікторович
dc.date.accessioned2024-12-10T18:28:32Z
dc.date.available2024-12-10T18:28:32Z
dc.date.issued2024
dc.description.abstractAs a result of the work performed, one of the types of MobileNet architecture of CNN artificial neural networks was applied in practice to solve the problem of gesture recognition in real time. The obtained results are important not only in the scientific sense, but also for practical application, because neural networks help people with various diseases, such as Parkinson's disease, speech or hearing impairment, tunnel syndrome, to facilitate their interaction with the computer, to carry out effective studying in schools and universities and, of course, socializing. So, these are just the first steps to simplify people's lives as much as possible and make it bright, despite certain limitations
dc.identifier.citationMazurets O., Zalutska O., Tyschenko O., Bohdanova A. An Approach to Using MobileNet CNN-model for Gesture Recognition. Proceedings of XXIII International Scientific and Practical Conference «Problems of Science and Technology: the Search for Innovative Solutions». May 15-17, 2024. Munich, Germany. 2024. Pp. 59-64
dc.identifier.urihttps://elar.khmnu.edu.ua/handle/123456789/17227
dc.language.isoen
dc.titleAn Approach to Using MobileNet CNN-model for Gesture Recognition
dc.typeСтаття
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