Arabic Sign Language – Quran Kareem Tracker with Streamlit (YOLOv8)

• Developed a real-time Arabic Sign Language recognition system for 32 letters using YOLOv8, achieving 99%

accuracy (mAP@50).

• Built to assist Quran Kareem learning for the deaf community with interactive gesture tracking.

• Deployed as a Streamlit web app for real-time detection with bounding boxes and confidence scores.

• Tools Used: Python, YOLOv8 (Ultralytics), Streamlit, OpenCV