Transfer Learning with DCNNs (DenseNet, Inception V3, Inception-ResNet V2, VGG16) for skin lesions classification on HAM10000 dataset largescale data.

[MICCAI 2023] ECL: Class-Enhancement Contrastive Learning for Long-tailed Skin Lesion Classification

Official implementation of MICCAI2024 paper "Evidential Concept Embedding Models: Towards Reliable Concept Explanations for Skin Disease Diagnosis"

AI-based localization and classification of skin disease with erythema

Data and code for our analysis of DermaMNIST (MedMNIST), HAM10000, and Fitzpatrick17k datasets

Skin Lesion Classification On Imbalanced Data Using Deep Learning With Soft Attention

A small Android application that determines a skin disease by a photo

MERN Stack Web Application "EpiDetect" which uses a fine-tuned ResNet50 model for skin disease detection.

An Effective Classification of Skin Infection using Deep Learning Techniques

This repository provides a deep learning-based approach to diagnose Melasma skin disease. By leveraging the power of deep neural networks, specifically VGGNet16, ResNet50, and AlexNet, this project aims to accurately classify Melasma images.

Predicting type of Skin Disease using CNN's . Deployed using Flask

Skin Disease Classifier

This repo contains the notebooks regarding our deep learning based image recognition projects with my students in Spelman College

This project focuses on building a model that predicts the age and contrasts amongst the medical images of skin diseases of 9 types. The dataset was taken from kaggle and was devided into train and validation images..

This project focuses on the recognition and analysis of various skin diseases, including cancer and Vitiligo, using advanced image processing techniques and machine learning models in Matlab.