Now showing items 1-3 of 3

    • A bio-inspired quaternion local phase CNN layer with contrast invariance and linear sensitivity to rotation angles 

      Moya Sánchez, Eduardo Ulises; Xambó Descamps, Sebastián; Sánchez Pérez, Abraham; Salazar Colores, Sebastián; Martínez Ortega, Jorge; Cortés García, Claudio Ulises (Elsevier, 2020-03)
      Article
      Open Access
      Deep learning models have been particularly successful with image recognition using Convolutional Neural Networks (CNN). However, the learning of a contrast invariance and rotation equivariance response may fail even with ...
    • Artificial intelligence to identify retinal fundus images, quality validation, laterality evaluation, macular degeneration, and suspected glaucoma 

      Zapata Victori, Miguel Ángel; Royo Fibla, Dídac; Font, Octavi; Vela Segarra, José Ignacio; Marcantonio Santa Cruz, Ivanna Andrea; Moya Sánchez, Eduardo Ulises; Sánchez Pérez, Abraham; Garcia Gasulla, Dario; Cortés García, Claudio Ulises; Ayguadé Parra, Eduard; Labarta Mancho, Jesús José (2020-02-13)
      Article
      Open Access
      Purpose: To assess the performance of deep learning algorithms for different tasks in retinal fundus images: (1) detection of retinal fundus images versus optical coherence tomography (OCT) or other images, (2) evaluation ...
    • Data augmentation for deep learning of non-mydriatic screening retinal fundus images 

      Moya Sánchez, Eduardo Ulises; Sánchez Pérez, Abraham; Zapata Victori, Miguel Ángel; Moreno, Jonatan; Garcia Gasulla, Dario; Parés, Ferran; Ayguadé Parra, Eduard; Labarta Mancho, Jesús José; Cortés García, Claudio Ulises (Springer, 2018)
      Conference report
      Restricted access - publisher's policy
      Fundus image is an effective and low-cost tool to screen for common retinal diseases. At the same time, Deep Learning (DL) algorithms have been shown capable of achieving similar or even better performance accuracies than ...