UdayTripathi108 / Comparison-of-different-Deep-Learning-Models-on-Skin-Disease-Classification Public

Notifications You must be signed in to change notification settings
Fork 0
Star 0

This is an empirical study on the working of different Deep Learning Models on Skin Disease Classification on Dermascopic images. It studies the working of models like CNN, ResNet, DenseNet, MobileNet, and, tells which model is better without hyperparameter tuning. the dataset used is from Kaggle.

0 stars 0 forks Branches Tags Activity

Notifications

Name		Name	Last commit message	Last commit date
Latest commit History 3 Commits
Deep_Leraning_Paper (1).pdf		Deep_Leraning_Paper (1).pdf
README.md		README.md
Skin_Disease.ipynb		Skin_Disease.ipynb

Repository files navigation

Comparison-of-different-Deep-Learning-Models-on-Skin-Disease-Classification

About

This is an empirical study on the working of different Deep Learning Models on Skin Disease Classification on Dermascopic images. It studies the working of models like CNN, ResNet, DenseNet, MobileNet, and, tells which model is better without hyperparameter tuning. the dataset used is from Kaggle.

skin machine-learning deep-neural-networks deep-learning machine-learning-algorithms cnn kaggle densenet machinelearning resnet deeplearning convolutional-neural-networks kaggle-dataset empirical-research skindiseaseclassification

Report repository

Releases

No releases published

Packages

No packages published

Languages

Jupyter Notebook 100.0%