Asl Detection Yolov5
A
Asl Detection Yolov5
Developed by niki-stha
A YOLOv5-based object detection model specifically designed for recognizing American Sign Language (ASL) gestures
Downloads 15
Release Time : 6/22/2023
Model Overview
This model is trained using the YOLOv5 architecture, capable of efficiently and accurately detecting American Sign Language gestures, suitable for sign language recognition and translation applications.
Model Features
High-precision Detection
Achieves an excellent mAP@0.5 score of 0.985 on the validation set
YOLOv5 Architecture
Utilizes the efficient YOLOv5 object detection architecture, balancing speed and accuracy
Easy to Use
Provides a simple Python interface for quick deployment and integration
Model Capabilities
Sign language gesture detection
Real-time object recognition
Image analysis
Use Cases
Accessibility Technology
Sign Language Translation System
Build real-time sign language translation applications to assist communication for the deaf and mute
Can accurately recognize multiple ASL gestures
Educational Technology
Sign Language Learning Assistant
Used in sign language learning applications to provide real-time feedback
Helps students master gestures correctly
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