Camila González

Orcid: 0000-0002-4510-7309

According to our database1, Camila González authored at least 22 papers between 2017 and 2024.

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



In proceedings 
PhD thesis 




Continual atlas-based segmentation of prostate MRI.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Semi-supervised learning for MALDI-TOF mass spectrometry data classification: an application in the salmon industry.
Neural Comput. Appl., May, 2023

Lifelong Learning in the Clinical Open World.
PhD thesis, 2023

Jointly Exploring Client Drift and Catastrophic Forgetting in Dynamic Learning.
CoRR, 2023

Med-NCA: Robust and Lightweight Segmentation with Neural Cellular Automata.
Proceedings of the Information Processing in Medical Imaging, 2023

Distance-based detection of out-of-distribution silent failures for Covid-19 lung lesion segmentation.
Medical Image Anal., 2022

i3Deep: Efficient 3D interactive segmentation with the nnU-Net.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022

Practical uncertainty quantification for brain tumor segmentation.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022

Task-Agnostic Continual Hippocampus Segmentation for Smooth Population Shifts.
Proceedings of the Domain Adaptation and Representation Transfer - 4th MICCAI Workshop, 2022

Disentanglement Enables Cross-Domain Hippocampus Segmentation.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

Improving Robustness and Calibration in Ensembles with Diversity Regularization.
Proceedings of the Pattern Recognition, 2022

Continual Hippocampus Segmentation with Transformers.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

Quality Monitoring of Federated Covid-19 Lesion Segmentation.
Proceedings of the Bildverarbeitung für die Medizin 2022, 2022

Self-supervised Out-of-distribution Detection for Cardiac CMR Segmentation.
Proceedings of the Medical Imaging with Deep Learning, 7-9 July 2021, Lübeck, Germany., 2021

Adversarial Continual Learning for Multi-domain Hippocampal Segmentation.
Proceedings of the Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health, 2021

Detecting When Pre-trained nnU-Net Models Fail Silently for Covid-19 Lung Lesion Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Semi-supervised learning for MS MALDI-TOF data.
Proceedings of the IEEE Latin American Conference on Computational Intelligence, 2021

How Reliable Are Out-of-Distribution Generalization Methods for Medical Image Segmentation?
Proceedings of the Pattern Recognition - 43rd DAGM German Conference, DAGM GCPR 2021, Bonn, Germany, September 28, 2021

M3d-CAM - A PyTorch Library to Generate 3D Attention Maps for Medical Deep Learning.
Proceedings of the Bildverarbeitung für die Medizin 2021, 2021

What is Wrong with Continual Learning in Medical Image Segmentation?
CoRR, 2020

M3d-CAM: A PyTorch library to generate 3D data attention maps for medical deep learning.
CoRR, 2020

Re-training Deep Neural Networks to Facilitate Boolean Concept Extraction.
Proceedings of the Discovery Science - 20th International Conference, 2017