HIGHLIGHTS
- What: This study investigates advances in vision-based HGR for HCI using DL methods and provides insights into the potential to enhance gesture recognition systems and shape the future of HCI. This proposed architecture, hereafter referred to as the Dynamic Adaptation Convolutional Neural_Network (DACNN), was compared with three other established models, focusing on the accuracy of each model as the primary metric for performance evaluation.
- Who: gerry from the SIMAD University, Department of Computing, Mogadishu, Somalia have published the paper: Dynamic Adaptation in Deep Learning for Enhanced Hand Gesture Recognition, in the Journal: (JOURNAL)
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