Applied SSD integrated with MobileNet model for object (sign gestures) detection and recognition and the model is trained using Transfer Learning, with the aim to develop a web app for real-time ASL recognition from user input & then to generate text in English.
This project applies Single-Shot Multibox Detector (SSD) architecture integrated with the mobilenetv2 model for the object(sign gestures) detection and recognition of Americal Sign Langguage (ASL) using Transfer Learning, with the aim to develop a web app for real-time ASL recognition from user input through vide frame & then to generate text in English.
The web App for neural network model is deployed in React and Flask.
Applied SSD integrated with MobileNet model for object (sign gestures) detection and recognition and the model is trained using Transfer Learning, with the aim to develop a web app for real-time ASL recognition from user input & then to generate text in English.