no code implementations • 13 Jul 2023 • Jorge Gonzalez-Zapata, Francisco Lopez-Tiro, Elias Villalvazo-Avila, Daniel Flores-Araiza, Jacques Hubert, Andres Mendez-Vazquez, Gilberto Ochoa-Ruiz, Christian Daul
The proposed Guided Deep Metric Learning approach is based on a novel architecture which was designed to learn data representations in an improved way.
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 • 5 Nov 2022 • Elias Villalvazo-Avila, Francisco Lopez-Tiro, Jonathan El-Beze, Jacques Hubert, Miguel Gonzalez-Mendoza, Gilberto Ochoa-Ruiz, Christian Daul
Moreover, in comparison to the state-of-the-art, the fusion of the deep features improved the overall results up to 11% in terms of kidney stone classification accuracy.
no code implementations • 1 Jun 2022 • Daniel Flores-Araiza, Francisco Lopez-Tiro, Elias Villalvazo-Avila, Jonathan El-Beze, Jacques Hubert, Gilberto Ochoa-Ruiz, Christian Daul
Identifying the type of kidney stones can allow urologists to determine their formation cause, improving the early prescription of appropriate treatments to diminish future relapses.
no code implementations • 31 May 2022 • Elias Villalvazo-Avila, Francisco Lopez-Tiro, Daniel Flores-Araiza, Gilberto Ochoa-Ruiz, Jonathan El-Beze, Jacques Hubert, 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.