This research enhances early disease diagnosis by analyzing retinal blood vessels in fundus images using deep learning. It employs eight pre-trained CNN models and Explainable AI techniques.

This repository contains an implementation of the ResNet101 architecture in PyTorch.

This repository focuses on classifying microscopic images of parasites using deep learning. It features a dataset of 15 parasitic classes, enhanced by Keras's image preprocessing and transfer learning with ResNet. The project aims to improve diagnostic capabilities in medical parasitology and has achieved great results in competitive evaluation.

Landmark Detection using pre-trained models.

Adopted a convolutional neural network for COVID-19 testing. Examined the performance of different pre-trained models on CT testing and identified that larger, out-of-field datasets boost the testing power of the models.