Volcanic Activity Classification Through Semi-Supervised Learning Applied to Satellite Radiance Time Series

Volcanic Activity Classification Through Semi-Supervised Learning Applied to Satellite Radiance Time Series

Satellite imagery provides a rich source of information that serves as a comprehensive and synoptic tool for the continuous monitoring of active volcanoes, including those in remote and inaccessible areas. The huge influx of such data requires the development of automated systems for efficient proce...

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Bibliographic Details
Main Authors: Francesco Spina, Giuseppe Bilotta, Annalisa Cappello, Marco Spina, Francesco Zuccarello, Gaetana Ganci
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Remote Sensing
Subjects:
classification algorithms
deep learning
generative adversarial networks
remote sensing
volcanic ash
Online Access:https://www.mdpi.com/2072-4292/17/10/1679
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