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Improving resilience of sensors in planetary exploration using data-driven models

Improving resilience of sensors in planetary exploration using data-driven models

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_crossref_primary_10_1088_2632_2153_acefaa

Improving resilience of sensors in planetary exploration using data-driven models

About this item

Full title

Improving resilience of sensors in planetary exploration using data-driven models

Publisher

Bristol: IOP Publishing

Journal title

Machine learning: science and technology, 2023-09, Vol.4 (3), p.35041

Language

English

Formats

Publication information

Publisher

Bristol: IOP Publishing

More information

Scope and Contents

Contents

Improving the resilience of sensor systems in space exploration is a key objective since the environmental conditions to which they are exposed are very harsh. For example, it is known that the presence of flying debris and Dust Devils on the Martian surface can partially damage sensors present in rovers/landers. The objective of this work is to sh...

Alternative Titles

Full title

Improving resilience of sensors in planetary exploration using data-driven models

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_crossref_primary_10_1088_2632_2153_acefaa

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_crossref_primary_10_1088_2632_2153_acefaa

Other Identifiers

ISSN

2632-2153

E-ISSN

2632-2153

DOI

10.1088/2632-2153/acefaa

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