Probabilistic machine learning for noisy labels in Earth observation

Label noise poses a significant challenge in Earth Observation (EO), often degrading the performance and reliability of supervised Machine Learning (ML) models. Yet, given the critical nature of several EO applications, developing robust and trustworthy ML solutions is essential. In this study, we t...

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Bibliographic Details
Published in:	Scientific reports Vol. 15; no. 1; pp. 35890 - 17
Main Authors:	Kondylatos, Spyros, Bountos, Nikolaos Ioannis, Prapas, Ioannis, Zavras, Angelos, Camps-Valls, Gustau, Papoutsis, Ioannis
Format:	Journal Article
Language:	English
Published:	London Nature Publishing Group UK 14.10.2025 Nature Publishing Group Nature Portfolio
Subjects:	639/166 639/705 Classification Datasets Decision making Deep learning Earth Emergency communications systems Epistemology Humanities and Social Sciences Learning algorithms Machine learning Mathematical models multidisciplinary Neural networks Science Science (multidisciplinary)
ISSN:	2045-2322, 2045-2322
Online Access:	Get full text
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