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All Journal Journal of Software Engineering, Information and Communication Technology
Ahmad Abuzar Alhamdani
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Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Application of Deep Learning using Convolutional Neural Network (CNN) Algorithm for Gesture Recognition Ahmad Abuzar Alhamdani
Journal of Software Engineering, Information and Communication Technology (SEICT) Vol 4, No 1: June 2023
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (396.587 KB) | DOI: 10.17509/seict.v2i1.34673

Abstract

Gesture recognition is a fascinating method of human-computer interaction that goes beyond traditional means such as keyboards, pointers, and joypads. In gesture recognition, Convolutional Neural Network (CNN) algorithms are utilized in Deep Learning to train models using datasets comprising gesture images. The training process involves pattern recognition and identification of crucial features from gesture images, followed by evaluation to measure the model's accuracy. Gesture recognition holds immense potential across various fields, including human-computer interaction, gaming, healthcare, and autonomous vehicles, and continues to be a focus of research and development in the future.
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