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This is a 5 Class Image Classification Task based on a Kaggle dataset from Eye Images (Aravind Eye hospital) - APTOS 2019 Challenge. The goal is to predict the Blindness Stage (0-4) class from the Eye retina Image using Deep Learning Models (CNN). This Automated System would speed up Blindness detection on Patients

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PriyaJ28/Automated-Diabetic-Retinopathy-Detection

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Automated-Diabetic-Retinopathy-Detection

This case study is based on a Kaggle dataset - https://www.kaggle.com/c/aptos2019-blindness-detection/

Here is the arXiv.org Research paper that was attempted to Implement - https://arxiv.org/pdf/2003.02261.pdf

Contents of the Code Files are given below :-

  1. Exploratory Data Analysis.ipynb : All Data Analysis & Insights on Images and classes
  2. Processing.ipynb : Image Resizing, preprocessing, data splitting [Image processing, Train/validation data]
  3. Resnet50 Colab Implementation.ipynb : Transfer Learning using ResNet50 [Complete Model and Evaluation]
  4. research_paper_implementation.ipynb : arXiv.org Research Paper Implementation

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This is a 5 Class Image Classification Task based on a Kaggle dataset from Eye Images (Aravind Eye hospital) - APTOS 2019 Challenge. The goal is to predict the Blindness Stage (0-4) class from the Eye retina Image using Deep Learning Models (CNN). This Automated System would speed up Blindness detection on Patients

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