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🔴 Approach : First Analyze the dataset by checking image quality, class distributions, and visualization of sample images. Then I train various models to enhance the classification accuracy, I propose building and comparing various models to select the best one. The models to be used include:
VGG /(Custom model)
ResNet
SEResNet
EfficientNet
Vision Transformer (ViT)
📍 Follow the Guidelines to Contribute in the Project :
You need to create a separate folder named as the Project Title.
Inside that folder, there will be four main components.
Images - To store the required images.
Dataset - To store the dataset or, information/source about the dataset.
Model - To store the machine learning model you've created using the dataset.
requirements.txt - This file will contain the required packages/libraries to run the project in other machines.
Inside the Model folder, the README.md file must be filled up properly, with proper visualizations and conclusions.
🔴🟡 Points to Note :
The issues will be assigned on a first come first serve basis, 1 Issue == 1 PR.
"Issue Title" and "PR Title should be the same. Include issue number along with it.
Follow Contributing Guidelines & Code of Conduct before start Contributing.
Deep Learning Simplified Repository (Proposing new issue)
🔴 Project Title : Skin Disease Classification using Deep Learning Models
🔴 Aim : To build a model to classify various Skin diseases
🔴 Dataset : https://www.kaggle.com/datasets/pacificrm/skindiseasedataset/data
🔴 Approach : First Analyze the dataset by checking image quality, class distributions, and visualization of sample images. Then I train various models to enhance the classification accuracy, I propose building and comparing various models to select the best one. The models to be used include:
VGG /(Custom model)
ResNet
SEResNet
EfficientNet
Vision Transformer (ViT)
📍 Follow the Guidelines to Contribute in the Project :
requirements.txt
- This file will contain the required packages/libraries to run the project in other machines.Model
folder, theREADME.md
file must be filled up properly, with proper visualizations and conclusions.🔴🟡 Points to Note :
✅ To be Mentioned while taking the issue :
Happy Contributing 🚀
All the best. Enjoy your open source journey ahead. 😎
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