Jacques Hubert

Orcid: 0000-0002-3807-0851

According to our database1, Jacques Hubert authored at least 21 papers between 2010 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Links

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Bibliography

2024
A metric learning approach for endoscopic kidney stone identification.
Expert Syst. Appl., 2024

Evaluating the plausibility of synthetic images for improving automated endoscopic stone recognition.
CoRR, 2024

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

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 in vivo recognition of kidney stones using machine learning.
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

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
Towards an automated classification method for ureteroscopic kidney stone images using ensemble learning.
Proceedings of the 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2020

2010
Subjective MPEG2 compressed video quality assessment: application to Tele-surgery.
Proceedings of the 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2010


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