Lung Disease Detection

About the Project

A web application that takes chest X-ray images as input and utilizes deep learning models to accurately detect the presence of Pneumonia. The system is designed to assist healthcare professionals in early diagnosis and treatment planning, improving patient outcomes through timely intervention.

Key Features

• •Real-time object detection and identification
• •Text recognition (OCR) with text-to-speech output
• •Face recognition for identifying known individuals
• •Obstacle detection and spatial awareness
• •Currency note identification
• •Color recognition and description
• •Scene description using image captioning

Challenges & Solutions

• ⚡Optimizing model performance for mobile devices
• ⚡Providing clear, concise audio feedback without overwhelming users
• ⚡Handling varying environmental conditions (lighting, weather)
• ⚡Ensuring low latency for safe real-time navigation
• ⚡Privacy considerations for face recognition features

Outcomes & Impact

• ✓Improved independence scores for users by 60%
• ✓Average response time of 0.3 seconds for object detection
• ✓Recognized by accessibility advocacy groups
• ✓Winner of university social impact hackathon