Sign Language Detection Using CNN- The need for accessible and reliable sign language detection has become increasingly important. Sign language is a critical mode of communication for the deaf and hard-of hearing communities, yet tools for real-time interpretation are limited and often inaccessible to the general public. This project aims to develop a software-based solution for sign language detection, using advanced image processing and computer vision techniques. Implemented in a Python-based Jupyter Notebook environment, the system uses hand tracking, gesture recognition, and machine learning algorithms such as Convolutional Neural Networks (CNN) to accurately identify and interpret sign language gestures.