Skin Cancer Detection Web App using Flask Framework deployed on the Heroku server.

We attempt to change how you look at Medical Diagnosis

Skin lesion classification, using Keras and the ISIC 2020 dataset

Pretraining and finetuning different vision transformer models on the ImageNet and Ham10000 dataset

Predict your diseases based on the symptoms provided And Image Processing technique is used to predict the skin cancer

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%. 🚀🚀

This repository contains Python code for generating a skin cancer detection model and utilizing it to detect skin cancer from user-inputted images or videos. The model architecture follows a sequential structure consisting of convolutional and pooling layers, with the final output layer using a sigmoid activation function.

A web app to detect Skin cancer using pictures of moles and other marks on skin