Francisco Javier Lopez-Tiro
Orcid: 0000-0003-1689-1998
According to our database1,
Francisco Javier Lopez-Tiro
authored at least 28 papers
between 2019 and 2024.
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Bibliography
2024
Expert Syst. Appl., 2024
Evaluating the plausibility of synthetic images for improving automated endoscopic stone recognition.
CoRR, 2024
Improving Prototypical Parts Abstraction for Case-Based Reasoning Explanations Designed for the Kidney Stone Type Recognition.
CoRR, 2024
IEEE Access, 2024
Image Enhancement and Segmentation of Magnetic Resonance Cerebral Vessels Through Conventional and Deep Learning Techniques.
Proceedings of the 37th IEEE International Symposium on Computer-Based Medical Systems, 2024
Evaluating the plausibility of synthetic images for improving automated endoscopic stone recognition.
Proceedings of the 37th IEEE International Symposium on Computer-Based Medical Systems, 2024
On the Link Between Model Performance and Causal Scoring of Medical Image Explanations.
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.
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.
CoRR, 2023
Improving automatic endoscopic stone recognition using a multi-view fusion approach enhanced with two-step transfer learning.
CoRR, 2023
Boosting Kidney Stone Identification in Endoscopic Images Using Two-Step Transfer Learning.
Proceedings of the Advances in Soft Computing, 2023
Improved Kidney Stone Recognition Through Attention and Multi-View Feature Fusion Strategies.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023
Improving Automatic Endoscopic Stone Recognition Using a Multi-view Fusion Approach Enhanced with Two-Step Transfer Learning.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
Deep Prototypical-Parts Ease Morphological Kidney Stone Identification and are Competitively Robust to Photometric Perturbations.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
2022
Improved Kidney Stone Recognition Through Attention and Multi-View Feature Fusion Strategies.
CoRR, 2022
Boosting Kidney Stone Identification in Endoscopic Images Using Two-Step Transfer Learning.
CoRR, 2022
Evaluating object detector ensembles for improving the robustness of artifact detection in endoscopic video streams.
CoRR, 2022
Interpretable Deep Learning Classifier by Detection of Prototypical Parts on Kidney Stones Images.
CoRR, 2022
Comparing feature fusion strategies for Deep Learning-based kidney stone identification.
CoRR, 2022
On the generalization capabilities of FSL methods through domain adaptation: a case study in endoscopic kidney stone image classification.
CoRR, 2022
On the Generalization Capabilities of FSL Methods Through Domain Adaptation: A Case Study in Endoscopic Kidney Stone Image Classification.
Proceedings of the Advances in Computational Intelligence, 2022
2021
Assessing deep learning methods for the identification of kidney stones in endoscopic images.
CoRR, 2021
Visualization of blood vessels in <i>in vitro</i> raw speckle images using an energy-based on DWT coefficients.
Biomed. Signal Process. Control., 2021
Proceedings of the IEEE International Instrumentation and Measurement Technology Conference, 2021
Assessing deep learning methods for the identification of kidney stones in endoscopic images.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021
2020
Effect of the Exposure Time in Laser Speckle Imaging for Improving Blood Vessels Localization: a Wavelet Approach.
Proceedings of the 2020 IEEE International Instrumentation and Measurement Technology Conference, 2020
2019
Visualization of in-vitro Blood Vessels in Contrast Images Based on Discrete Wavelet Transform Decomposition.
Proceedings of the IEEE International Instrumentation and Measurement Technology Conference, 2019