# Chest X-ray Classification

An image classification model fine-tuned on a chest X-ray dataset, achieving 97.13% accuracy

A deep learning model based on ViT architecture for identifying pneumonia symptoms in chest X-ray images

This model is a fine-tuned version of Google's ViT-base model on a chest X-ray classification dataset, designed for medical image analysis.

A pneumonia detection model based on the ViT architecture, fine-tuned on a chest X-ray classification dataset with an accuracy rate of 97.68%

A convolutional neural network based on the DenseNet architecture, specifically designed for X-ray image classification tasks, achieving dense inter-layer connections through dense blocks.

A pre-trained model based on the DenseNet121 architecture, specifically designed for chest X-ray image classification tasks with 18 output targets.