🤟 ASL Recognizer: A real-time American Sign Language translation system utilizing MediaPipe for hand-landmark extraction and Deep Learning for gesture classification.
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Updated
Nov 7, 2025 - Jupyter Notebook
🤟 ASL Recognizer: A real-time American Sign Language translation system utilizing MediaPipe for hand-landmark extraction and Deep Learning for gesture classification.
Real-time Sign Language Recognition system using a CNN model to translate 36 hand gestures into text with 95%+ accuracy.
Real-time Hand Sign Language Detection System using Teachable Machine, TensorFlow, OpenCV, and CVZone. Recognizes ASL alphabet gestures (A–Z) through webcam-based hand tracking and deep learning.
Machine learning based sign language recognition system that detects hand gestures and converts them into text and speech.
Modular Computer Vision project for hand gesture recognition, sign language interpretation, and air-writing with integrated text-to-speech and automated emergency email alerts.
Real-time American Sign Language (ASL) recognition system using PyTorch and MediaPipe. Recognizes 25 common ASL gestures with 76.05% accuracy, optimized for RTX4070 GPUs. Features live webcam recognition, hybrid TCN+LSTM+Transformer architecture, and comprehensive training pipeline.
Real-time American Sign Language recognition using ResNet50 + Vision Transformer with 99.93% accuracy.
Real-time American Sign Language gesture recognition system using MediaPipe hand landmarks and Random Forest classification.
SpeakSign AI is a real-time Voice-to-Sign Language Translator & ASL Gesture Recognition Web Studio built with Python, Flask, TensorFlow (CNN), and Web Speech API. 🤟 Real-time speech-to-sign conversion & live webcam gesture classification.
AI-powered American Sign Language (ASL) recognition system that translates hand gestures into readable English text in real-time.
Real-time American Sign Language (ASL) detection system using Deep Learning (29 classes). Built with TensorFlow/Keras and OpenCV.
Real-time ASL Recognition Web App using MediaPipe & Machine Learning (RF, SVM, KNN). Features a unique Dual-Hand HCI mechanism for touchless typing.
Mobile-first ASL fingerspelling trainer powered by MediaPipe. Earn a shareable certificate. Camera stays in your browser.
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