Comparative Evaluation of Pretrained Models for Lung Disease Classification

This project evaluates pretrained CNNs, including EfficientNetV2 and VGG models, for multi-class lung disease classification using chest X-rays. It compares Adam and AdamW optimizers on a dataset of 5,000 images, aiming to enhance diagnostic accuracy.

Project Type: Model