A real-time American Sign Language (ASL) to text chat application with a pink-themed UI, powered by a Convolutional Neural Network (CNN) that recognizes 29 classes (A-Z plus delete, space, and nothing). The app uses MediaPipe for hand landmark detection and TensorFlow for sign classification.

Implementation of CNN using tensorFlow on Handsign Dataset

Use of Convolutional Neural Networks to classify images from Sign Language MNIST dataset, with hands depicting the 26 letters of the English alphabet. From the course Convolutional Neural Networks in TensorFlow, DeepLearning.AI, Coursera, Week 4 - Multiclass Classifications

Sign_Language_Recognition_using_DeepLearning is a real-time hand gesture recognition system that uses OpenCV for hand tracking and a Convolutional Neural Network (CNN) model built with TensorFlow/Keras for gesture classification. The project is designed to recognize and classify various sign language gestures through a live webcam feed.