Cad-eye: an automated system for multi-eye disease classification using feature fusion with deep learning models and fluorescence imaging for enhanced interpretability

HIGHLIGHTS

• What: In this work, a novel DL model that combines the features extracted from two of the most efficient DL models is proposed. The aim of this robust model and huge dataset was enhancing the accuracy and reliability of retinal classification systems. In this work, a new dataset was collected from reputable internet websites and a private collected dataset from previous research. This work proposes a novel deep learning (DL) model to address the problem of recognizing four different eye diseases.
• Who: Maimoona Khalid et al. from the Department of Computer Software Engineering, Military College . . .
  

   

  

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