48 citations · 57 across the 3 of their papers we have counts for
3 papers
On the generalization capabilities of FSL methods through domain adaptation: a case study in endoscopic kidney stone image classification
Mauricio Mendez-Ruiz, Francisco Lopez-Tiro, Jonathan El-Beze +5
Deep learning has shown great promise in diverse areas of computer vision, such as image classification, object detection and semantic segmentation, among many others. However, as…
On the in vivo recognition of kidney stones using machine learning
Francisco Lopez-Tiro, Vincent Estrade, Jacques Hubert +4
Determining the type of kidney stones allows urologists to prescribe a treatment to avoid recurrence of renal lithiasis. An automated in-vivo image-based classification method woul…
Assessing deep learning methods for the identification of kidney stones in endoscopic images
Francisco Lopez, Andres Varela, Oscar Hinojosa +8
Knowing the type (i.e., the biochemical composition) of kidney stones is crucial to prevent relapses with an appropriate treatment. During ureteroscopies, kidney stones are fragmen…