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Hybrid Model for Cataract Detection by devswagata2 is a document available to read on EtoBox.

What is Hybrid Model for Cataract Detection about?

The document outlines a hybrid model for classifying retinal OCT images using a combination of VGG19 and ResNet50 architectures, leveraging transfer learning to extract deep spatial features. The model achieved an accuracy of 98%, outperforming standalone models, with improved recall for cataract detection. Data augmentation techniques were applied to enhance the dataset, and the model was trained using binary cross-entropy loss with optimized hyperparameters.

Author

devswagata2

Language

EN