Customizable Sign Language Gesture Prediction for Assistive Devices Using Machine Learning

Abstract

Abstract: The objective of this investigate consider is to move forward human-computer interaction by presenting an progressed machine learning approach that predicts hand developments inreal-time. By utilizing a mix of computer vision and cutting-edge models such as CNNs and RNNs, the framework shows exact comprehension of different hand signals. Assessments uncover that exchange learning and information increase strategies move forward show generalization. Emphasizing the conceivable impact on areas such as robots and virtual reality, the think about gives a premise for future advancements in user-friendly HCI