Mobile-Net Based Pneumonia Detection Model

Pneumonia, a leading global cause of mortality, requires timely and accurate diagnosis to mitigate its impact. This work introduces an automated pneumonia detection system using MobileNet, a lightweight Convolutional Neural Network (CNN) optimized for mobile and embedded devices. By employing depth wise separable convolutions, Mobile Net reduces computational complexity while maintaining high accuracy. Trained on a labelled chest X-ray dataset with preprocessing techniques, it achieves 92.5% accuracy, 91.8% precision, and 93.2% recall, offering an efficient, accessible solution for resource-constrained healthcare settings.