Enhancing space sensor resilience with transfer learning in data-scarce scenarios

Enhancing space sensor resilience with transfer learning in data-scarce scenarios

In Mars exploration missions, harsh environmental conditions, such as those generated by dust devils, can damage sensing systems. Soft sensors offer a promising solution in such scenarios, but their implementation is challenging when data is scarce. This paper explores the use of transfer learning (...

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Bibliographic Details
Main Authors: Dileep Kumar, Manuel Domínguez-Pumar, Beatriz Otero-Calviño, Joan Pons-Nin, Josefina Torres, Mercedes Marín, Javier Gómez-Elvira, Luis Mora, Sara Navarro, Jose Rodríguez-Manfredi
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:Machine Learning: Science and Technology
Subjects:
Martian wind sensors
soft sensors
deep learning
transfer learning
small dataset
Online Access:https://doi.org/10.1088/2632-2153/adfd38
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