Daniel Flores-Araiza

According to our database, Daniel Flores-Araiza authored at least 18 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2024

A metric learning approach for endoscopic kidney stone identification.

Jorge Gonzalez-Zapata, Francisco Javier Lopez-Tiro, Elias Villalvazo-Avila, Daniel Flores-Araiza, Jacques Hubert, Gilberto Ochoa-Ruiz, Christian Daul, Andres Mendez-Vazquez

Expert Syst. Appl., 2024

Improving Prototypical Parts Abstraction for Case-Based Reasoning Explanations Designed for the Kidney Stone Type Recognition.

Daniel Flores-Araiza, Francisco Javier Lopez-Tiro, Clément Larose, Salvador Hinojosa, Andres Mendez-Vazquez, Miguel González-Mendoza, Gilberto Ochoa-Ruiz, Christian Daul

CoRR, 2024

On the In Vivo Recognition of Kidney Stones Using Machine Learning.

Francisco Javier Lopez-Tiro, Vincent Estrade, Jacques Hubert, Daniel Flores-Araiza, Miguel González-Mendoza, Gilberto Ochoa, Christian Daul

IEEE Access, 2024

On the Link Between Model Performance and Causal Scoring of Medical Image Explanations.

Daniel Flores-Araiza, Armando Villegas-Jimenez, Francisco Javier Lopez-Tiro, Miguel González-Mendoza, Rosa-Maria Rodríguez-Guéant, Jacques Hubert, Gilberto Ochoa-Ruiz, Christian Daul

Proceedings of the 37th IEEE International Symposium on Computer-Based Medical Systems, 2024

2023

Causal Scoring Medical Image Explanations: A Case Study On Ex-vivo Kidney Stone Images.

Armando Villegas-Jimenez, Daniel Flores-Araiza, Francisco Javier Lopez-Tiro, Gilberto Ochoa-Ruiz, Christian Daul

CoRR, 2023

SuSana Distancia is all you need: Enforcing class separability in metric learning via two novel distance-based loss functions for few-shot image classification.

Mauricio Mendez-Ruiz, Jorge Gonzalez-Zapata, Iván Reyes-Amezcua, Daniel Flores-Araiza, Francisco Javier Lopez-Tiro, Andres Mendez-Vazquez, Gilberto Ochoa-Ruiz

CoRR, 2023

Image Captioning for Automated Grading and Understanding of Ulcerative Colitis.

Flor Helena Valencia, Daniel Flores-Araiza, Obed Cerda, Venkataraman Subramanian, Thomas de Lange, Gilberto Ochoa-Ruiz, Sharib Ali

Proceedings of the Cancer Prevention Through Early Detection, 2023

Assessing the Performance of Deep Learning-Based Models for Prostate Cancer Segmentation Using Uncertainty Scores.

Pablo Cesar Quihui-Rubio, Daniel Flores-Araiza, Gilberto Ochoa-Ruiz, Miguel González-Mendoza, Christian Mata

Proceedings of the Cancer Prevention Through Early Detection, 2023

FAU-Net: An Attention U-Net Extension with Feature Pyramid Attention for Prostate Cancer Segmentation.

Pablo Cesar Quihui-Rubio, Daniel Flores-Araiza, Miguel González-Mendoza, Christian Mata, Gilberto Ochoa-Ruiz

Proceedings of the Advances in Soft Computing, 2023

Boosting Kidney Stone Identification in Endoscopic Images Using Two-Step Transfer Learning.

Francisco Javier Lopez-Tiro, Daniel Flores-Araiza, Juan Pablo Betancur-Rengifo, Iván Reyes-Amezcua, Jacques Hubert, Gilberto Ochoa-Ruiz, Christian Daul

Proceedings of the Advances in Soft Computing, 2023

Deep Prototypical-Parts Ease Morphological Kidney Stone Identification and are Competitively Robust to Photometric Perturbations.

Daniel Flores-Araiza, Francisco Javier Lopez-Tiro, Jonathan El Beze, Jacques Hubert, Miguel González-Mendoza, Gilberto Ochoa-Ruiz, Christian Daul

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Interpretable Deep Learning Classifier by Detection of Prototypical Parts on Kidney Stones Images.

Daniel Flores-Araiza, Francisco Javier Lopez-Tiro, Elias Villalvazo-Avila, Jonathan El Beze, Jacques Hubert, Gilberto Ochoa-Ruiz, Christian Daul

CoRR, 2022

Comparing feature fusion strategies for Deep Learning-based kidney stone identification.

Elias Villalvazo-Avila, Francisco Javier Lopez-Tiro, Daniel Flores-Araiza, Gilberto Ochoa-Ruiz, Jonathan El Beze, Jacques Hubert, Christian Daul

CoRR, 2022

On the in vivo recognition of kidney stones using machine learning.

Gilberto Ochoa-Ruiz, Vincent Estrade, Francisco Javier Lopez-Tiro, Daniel Flores-Araiza, Jonathan El Beze, Dinh Hoan Trinh, Miguel González-Mendoza, Pascal Eschwege, Jacques Hubert, Christian Daul

CoRR, 2022

MACFE: A Meta-learning and Causality Based Feature Engineering Framework.

Iván Reyes-Amezcua, Daniel Flores-Araiza, Gilberto Ochoa-Ruiz, Andres Mendez-Vazquez, Eduardo Rodriguez-Tello

Proceedings of the Advances in Computational Intelligence, 2022

On the Generalization Capabilities of FSL Methods Through Domain Adaptation: A Case Study in Endoscopic Kidney Stone Image Classification.

Mauricio Mendez-Ruiz, Francisco Javier Lopez-Tiro, Daniel Flores-Araiza, Jonathan El Beze, Gilberto Ochoa-Ruiz, Miguel González-Mendoza, Jacques Hubert, Andres Mendez-Vazquez, Christian Daul

Proceedings of the Advances in Computational Intelligence, 2022

Guided Deep Metric Learning.

Jorge Gonzalez-Zapata, Iván Reyes-Amezcua, Daniel Flores-Araiza, Mauricio Mendez-Ruiz, Gilberto Ochoa-Ruiz, Andres Mendez-Vazquez

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2014

Identification and PID control for a quadrocopter.

Illiani Carro-Pérez, Daniel Flores-Araiza, Jesús Anselmo Fortoul-Díaz, Raúl Maximo, Hugo G. González-Hernández

Proceedings of the 24th International Conference on Electronics, 2014