no code implementations • 15 May 2023 • Mauricio Mendez-Ruiz, Jorge Gonzalez-Zapata, Ivan Reyes-Amezcua, Daniel Flores-Araiza, Francisco Lopez-Tiro, Andres Mendez-Vazquez, Gilberto Ochoa-Ruiz
Few-shot learning is a challenging area of research that aims to learn new concepts with only a few labeled samples of data.
no code implementations • 6 Apr 2023 • Francisco Lopez-Tiro, Elias Villalvazo-Avila, Juan Pablo Betancur-Rengifo, Ivan Reyes-Amezcua, Jacques Hubert, Gilberto Ochoa-Ruiz, Christian Daul
This contribution presents a deep-learning method for extracting and fusing image information acquired from different viewpoints, with the aim to produce more discriminant object features for the identification of the type of kidney stones seen in endoscopic images.
no code implementations • 24 Oct 2022 • Francisco Lopez-Tiro, Juan Pablo Betancur-Rengifo, Arturo Ruiz-Sanchez, Ivan Reyes-Amezcua, Jonathan El-Beze, Jacques Hubert, Michel Daudon, Gilberto Ochoa-Ruiz, Christian Daul
Finally, in comparison to models that are trained from scratch or by initializing ImageNet weights, the obtained results suggest that the two-step approach extracts features improving the identification of kidney stones in endoscopic images.
1 code implementation • 8 Jul 2022 • Ivan Reyes-Amezcua, Daniel Flores-Araiza, Gilberto Ochoa-Ruiz, Andres Mendez-Vazquez, Eduardo Rodriguez-Tello
Feature engineering has become one of the most important steps to improve model prediction performance, and to produce quality datasets.
no code implementations • 4 Jun 2022 • Jorge Gonzalez-Zapata, Ivan Reyes-Amezcua, Daniel Flores-Araiza, Mauricio Mendez-Ruiz, Gilberto Ochoa-Ruiz, Andres Mendez-Vazquez
Deep Metric Learning (DML) methods have been proven relevant for visual similarity learning.