A computer vision-based sign language recognition system using MediaPipe and neural networks to classify static and dynamic hand gestures for real-time applications.

The course project focuses on hand gesture classification using transfer learning.

A deep learning project for hand gesture classification using the HAGRID dataset. It features a modular and reproducible pipeline for data preprocessing, model training, and evaluation while benchmarking CNN- and Transformer-based architectures for gesture recognition.