Speakers
Cosmin Sabo
(Universitas Foundation)
Voicu Babiciu
(Universitatea Tehnica din Cluj Napoca, Centru Universitar Nord din Baia Mare)Prof.
Ștefan Vasile Oniga
(Universitatea Tehnica din Cluj Napoca, Centru Universitar Nord din Baia Mare)
Description
Hand gesture recognition is crucial to human-computer interaction, enabling seamless communication with machines. Electromyographic (EMG) signals, which capture muscle activity, provide a rich source of information for hand gesture classification. However, EMG signals are often contaminated by noise and exhibit variability, posing challenges for accurate classification. This research proposes a novel approach to hand gesture classification using a 1D Convolutional Neural Network (1D CNN) model.
Primary author
Voicu Babiciu
(Universitatea Tehnica din Cluj Napoca, Centru Universitar Nord din Baia Mare)
Co-authors
Cosmin Sabo
(Universitas Foundation)
Prof.
Ștefan Vasile Oniga
(Universitatea Tehnica din Cluj Napoca, Centru Universitar Nord din Baia Mare)
