Improving glaucoma diagnosis assembling deep networks and voting schemes

HIGHLIGHTS

• who: Adriu00e1n Su00e1nchez-Morales and colleagues from the Departamento de Tecnologu00edas de la Informaciu00f3n y las Comunicaciones, Campus Muralla del Mar have published the Article: Improving Glaucoma Diagnosis Assembling Deep Networks and Voting Schemes, in the Journal: Diagnostics 2022, 12, 1382. of /2022/
• what: The authors propose a novel soft voting method that combines the probability of class membership obtained by three different machine_learning models: CNN, CapsNet and CAE. The authors focus on deep Convolutional Denoising Autoencoders (CDAE), as they are the right version to model and classify image data. In this work, a fourth . . .
  

   

  

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