Miguel Monteiro

Orcid: 0000-0003-1530-4122

According to our database1, Miguel Monteiro authored at least 15 papers between 2018 and 2023.

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

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
Study of JavaScript Static Analysis Tools for Vulnerability Detection in Node.js Packages.
IEEE Trans. Reliab., December, 2023

High Fidelity Image Counterfactuals with Probabilistic Causal Models.
Proceedings of the International Conference on Machine Learning, 2023

Measuring axiomatic soundness of counterfactual image models.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Structured Uncertainty in the Observation Space of Variational Autoencoders.
Trans. Mach. Learn. Res., 2022

Multispectral vineyard segmentation: A deep learning comparison study.
Comput. Electron. Agric., 2022

Analysing the effectiveness of a generative model for semi-supervised medical image segmentation.
Proceedings of the Machine Learning for Health, 2022

Automatic Lesion Analysis for Increased Efficiency in Outcome Prediction of Traumatic Brain Injury.
Proceedings of the Machine Learning in Clinical Neuroimaging - 5th International Workshop, 2022

Safe Roads: an Integration between Twitter and City Sensing.
Proceedings of the 12th International Conference on the Internet of Things, 2022

2021
Active label cleaning: Improving dataset quality under resource constraints.
CoRR, 2021

Multispectral Vineyard Segmentation: A Deep Learning approach.
CoRR, 2021

Pharmacy Electronic Records and Patient Clustering: Exploring New Ways to Increase the Provision of Tailored Pharmaceutical Services.
Proceedings of the Public Health and Informatics, 2021

2020
Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019
TBI Lesion Segmentation in Head CT: Impact of Preprocessing and Data Augmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2019

2018
Using Machine Learning to Improve the Prediction of Functional Outcome in Ischemic Stroke Patients.
IEEE ACM Trans. Comput. Biol. Bioinform., 2018

Conditional Random Fields as Recurrent Neural Networks for 3D Medical Imaging Segmentation.
CoRR, 2018


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