no code implementations • 23 Nov 2021 • Gabriel García, Adrián Colomer, Rafael Verdú-Monedero, José Dolz, Valery Naranjo
Particularly, the proposed two-step learning methodology resorts to pseudo-labels generated during the first step to augment the training dataset on the target domain, which is then used to train the final target model.
no code implementations • 25 Jun 2021 • Gabriel García, Rocío del Amor, Adrián Colomer, Rafael Verdú-Monedero, Juan Morales-Sánchez, Valery Naranjo
Glaucoma is one of the leading causes of blindness worldwide and Optical Coherence Tomography (OCT) is the quintessential imaging technique for its detection.
no code implementations • 25 Jun 2021 • Gabriel García, Anna Esteve, Adrián Colomer, David Ramos, Valery Naranjo
Recently, bladder cancer has been significantly increased in terms of incidence and mortality.
no code implementations • 21 May 2021 • Julio Silva-Rodríguez, Elena Payá-Bosch, Gabriel García, Adrián Colomer, Valery Naranjo
Prostate cancer is one of the most prevalent cancers worldwide.
no code implementations • 9 Sep 2020 • Gabriel García, Adrián Colomer, Valery Naranjo
Taking into account that glaucoma is the leading cause of blindness worldwide, we propose in this paper three different learning methodologies for glaucoma detection in order to elucidate that traditional machine-learning techniques could outperform deep-learning algorithms, especially when the image data set is small.
no code implementations • 29 May 2020 • Gabriel García, Rocío del Amor, Adrián Colomer, Valery Naranjo
Nowadays, glaucoma is the leading cause of blindness worldwide.