Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Abraham Sánchez Pérez"'
Autor:
Sebastià Xambó-Descamps, Ulises Cortés, Sebastián Salazar-Colores, Abraham Sánchez Pérez, Jorge Martínez-Ortega, E. Ulises Moya-Sánchez
Publikováno v:
Pattern Recognition Letters. 131:56-62
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 very deep CNNs or by large d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ed828496e48fcc253b41e9578192fa10
https://doi.org/10.1016/j.patrec.2019.12.001
https://doi.org/10.1016/j.patrec.2019.12.001
Autor:
Eduard Ayguadé, Ivanna Marcantonio, Octavi Font, Abraham Sánchez-Pérez, Eduardo Ulises Moya-Sánchez, José I. Vela, Ulises Cortés, Miguel A Zapata, Dídac Royo-Fibla, Jesús Labarta, Dario Garcia-Gasulla
Publikováno v:
Clinical Ophthalmology. 14:419-429
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 of good quality retinal fundu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::638b5fab9de5e2a12310dd5d34566ecb
https://doi.org/10.2147/opth.s235751
https://doi.org/10.2147/opth.s235751
Autor:
Eduardo Ulises Moya-Sánchez, Sebastià Xambó-Descamps, Sebastián Salazar Colores, Ulises Cortés, Abraham Sánchez Pérez
Publikováno v:
Systems, Patterns and Data Engineering with Geometric Calculi ISBN: 9783030744854
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
Deep learning (DL) is attracting considerable interest as it currently achieves remarkable performance in many branches of science and technology. However, current DL cannot guarantee capabilities of the mammalian visual systems such as lighting chan
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5df3bdbde4eb6068beb70fc6997323dc
https://hdl.handle.net/2117/349717
https://hdl.handle.net/2117/349717
Autor:
E. Ulises Moya-Sanchez, Sebastia Xambo-Descamps, Abraham Sanchez Perez, Sebastian Salazar-Colores, Ulises Cortes
Publikováno v:
IEEE Access, Vol 9, Pp 163735-163746 (2021)
At present, Convolutional Neural Networks (ConvNets) achieve remarkable performance in image classification tasks. However, current ConvNets cannot guarantee the capabilities of mammalian visual systems such as invariance to contrast and illumination
Externí odkaz:
https://doaj.org/article/8cc8f641aee847f088c9f95b929b9811