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deep learning project designed to assist in the early detection of diabetic retinopathy, a leading cause of blindness in diabetic patients. Leveraging the power of transfer learning, this project employs five distinct pre-trained models on a custom dataset, offering accurate and efficient predictions for diabetic retinopathy severity.

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AhmadMaazz/Diagnosing-Diabetic-Retinopathy-Using-Deep-Learning

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Diabetic Retinopathy Diagnosis with Transfer Learning

Deep learning project aimed at early detection of diabetic retinopathy, a leading cause of blindness in diabetic patients. By employing transfer learning, I have integrated five pre-trained models - VGG16, ResNet50, InceptionV3, MobileNetV2, and EfficientNetB0 - to make accurate predictions on a custom dataset created for this purpose.

Key Features

Transfer Learning Expertise: Utilizing state-of-the-art pre-trained models for robust and accurate predictions.

Custom Dataset: A meticulously curated dataset ensures the models are trained on diverse and real-world diabetic retinopathy cases.

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deep learning project designed to assist in the early detection of diabetic retinopathy, a leading cause of blindness in diabetic patients. Leveraging the power of transfer learning, this project employs five distinct pre-trained models on a custom dataset, offering accurate and efficient predictions for diabetic retinopathy severity.

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