Handy makes defining and recognizing custom hand poses in WebXR a snap!

Real-time AI-powered translation of American Sign Language fingerspelling (sign to text)

Sign Language Detection system based on computer vision and deep learning using OpenCV and Tensorflow/Keras frameworks.

Sign Language Recognition using WiFi and Convolutional Neural Networks

Real-time fingerspelling video recognition achieving 74.4% letter accuracy on ChicagoFSWild+

To detect American Sign Language in real-time.

World Level American Sign Language Recognition and Translation to Spoken Language

The application is developed using Python3, OpenCV and with concepts of Neural Networks it is trained on DarkNet 53 and for the real time object detection I am using Yolo v3. It detects the 1 hand representation of number 1-10 which will be pointed by the user in real time using American Sign Language

American Sign Language Detection Android App using SSD_Mobilenet | Google Colab

An Android Application that uses gesture recognition to understand alphabets of american sign language

A CNN based human computer interface for American Sign Language recognition for hearing-impaired individuals

communication application to make Complete conversation with deaf people

Recognise and Learn American Sign Language

A simple sign language recognizer using SVM

Translate American Sign Language using your iPhone's camera!

🧏 Detection of the alphabets in American Sign Language (ASL).

Real-time American Sign Language (ASL) letters detection, via PyTorch, OpenCV, YOLOv5, Roboflow and LabelImg 🤟

Sign language recognition, using multihand tracking solution from Mediapipe, along with Speech recognition and Text to Speech to deliver an Android App for deaf mute people

Convolution Neural Network to perform classification of various Fingerspelling gestures in American Sign Language

Portable sign language (ASL) recognition device that utilizes real-time and efficient programming to help mute and deaf by establishing two-way communication channel with people who have never studied sign language.