🧠 Diabetic Retinopathy Detection – CNN-Based Classifier

A deep learning-based solution for early detection of diabetic retinopathy using convolutional neural networks (CNNs). This model achieves over 95% precision in classifying retinal disorders from medical images.

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📌 Features

• 🔬 Detects diabetic retinopathy from retina images
• 🧠 Built with CNN using TensorFlow and Keras
• 🗃️ Preprocessed and augmented dataset for robust learning
• 📈 Achieved 95%+ precision in evaluation
• 👥 Developed collaboratively as part of an academic research project

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🛠️ Tech Stack

• Language: Python
• Frameworks: TensorFlow, Keras
• Tools: NumPy, Matplotlib, OpenCV
• Others: Scikit-learn, ImageDataGenerator for augmentation

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📂 Project Structure

diabetic-retinopathy-main/ ├── dataset/ # Retina images ├── model/ # Saved model and architecture ├── notebooks/ # Training & evaluation notebooks ├── utils/ # Image preprocessing and helpers ├── main.py # Training script ├── requirements.txt └── README.md