[MICCAI 2023] DermoSegDiff: A Boundary-aware Segmentation Diffusion Model for Skin Lesion Delineation

FixCaps: An Improved Capsules Network for Diagnosis of Skin Cancer，DOI: 10.1109/ACCESS.2022.3181225

Official repository of ICML 2023 paper: Dividing and Conquering a BlackBox to a Mixture of Interpretable Models: Route, Interpret, Repeat

The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions.

This repo includes classifier trained to distinct 7 type of skin lesions

Multiclass skin cancer detection using explainable AI for checking the models' robustness

This is a project that I worked on with my colleagues in the 6th Semester of my B.tech. In this project, we present a fully automatic method for skin lesion segmentation by leveraging UNet and FCN that is trained end to-end. For Skin lesion disease classification, we use a customized convolutional neural net. Designing a novel loss function base…

Cross-platform smartphone app capable of detecting skin cancer lesions using Computer Vision.

Convolutional neural network capable of identifying skin lesions (based on the skin lesion image data set HAM10000).

Notebooks of pre trained models using the HAM10000 dataset

This project uses TensorFlow to implement a Convolutional Neural Network (CNN) for image classification. The goal is to classify skin lesion images into different categories. The dataset used is HAM10000, which contains skin lesion images with associated metadata. The actual accuracy of the model is 90%. 🚀🚀

Skin Cancer MNIST: HAM10000 - ResNet50 vs Inception-V3 vs VGG-19 vs VGG-16 vs GoogLeNet (Inception-V1)

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

This project is designed for classifying various skin diseases using the HAM10000 dataset. It leverages a trained model, explains predictions using LIME, and provides multiple interfaces for users, including a server, a graphical user interface, a command-line interface, and an API.

HAM10000 image dataset classification using Pytorch and Scikit Learn

Terminal application to perform skin lesion segmentation & classification

Diagnosis of Dermoscopic Images using Multi-Sizing Ensemble-Based Deep Learning Method

Discover DermaScan: A full-stack web app with MobileNetV2-based skin lesion classifier using Harvard's Ham10000 Dataset for precise dermatological diagnosis.

This is for Final Project of Theoretical Machine Learning Course...