Pneumonia X-Ray Classification

A deep learning project that implements and compares three neural network models for automated pneumonia detection from chest X-ray images.

Implements a Simple Neural Network, a CNN, and a CNN with Residual Connections to study how model complexity affects medical image classification.

Features data augmentation, early stopping, batch normalization, and dropout for robust training on a medical imaging dataset.

Built with TensorFlow/Keras, OpenCV, and scikit-learn with comprehensive evaluation using confusion matrices and classification reports.