Abstract
This paper presents a novel application of fuzzy-rough setbased
feature selection (FRFS) for Mars terrain image classification. The
work allows the induction of low-dimensionality feature sets from sample
descriptions of feature patterns of a much higher dimensionality. In particular,
FRFS is applied in conjunction with multi-layer perceptron and
K-nearest neighbor based classifiers. Supported with comparative studies,
the paper demonstrates that FRFS helps to enhance the effectiveness
and efficiency of conventional classification systems, by minimizing redundant
and noisy features. This is of particular significance for on-board
image classification in future Mars rover missions.
Original language | English |
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Title of host publication | Rough Sets, Fuzzy Sets, Data Mining and Granular Computing |
Publisher | Springer Nature |
Pages | 209-216 |
Number of pages | 8 |
ISBN (Electronic) | 978-3-642-10646-0 |
ISBN (Print) | 978-3-642-10645-3 |
DOIs | |
Publication status | Published - 2009 |
Event | 12th International Conference, RSFDGrC 2009 - Delhi, India Duration: 15 Dec 2009 → 18 Dec 2009 |
Conference
Conference | 12th International Conference, RSFDGrC 2009 |
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Country/Territory | India |
City | Delhi |
Period | 15 Dec 2009 → 18 Dec 2009 |