Minimum class variance broad learning system for hyperspectral image classification (Englisch)
Freier Zugriff
- Neue Suche nach: Chen, Peng
- Neue Suche nach: Chen, Peng
In:
IET Image Processing
;
14
, 13
;
3039-3045
;
2020
- Aufsatz (Zeitschrift) / Elektronische Ressource
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Titel:Minimum class variance broad learning system for hyperspectral image classification
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Beteiligte:Chen, Peng ( Autor:in )
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Erschienen in:IET Image Processing ; 14, 13 ; 3039-3045
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Verlag:
- Neue Suche nach: The Institution of Engineering and Technology
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Erscheinungsdatum:01.11.2020
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Format / Umfang:7 pages
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ISSN:
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DOI:
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Medientyp:Aufsatz (Zeitschrift)
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Format:Elektronische Ressource
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Sprache:Englisch
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Schlagwörter:hyperspectral datasets , HSI classification , image representation , geophysical image processing , minimum class variance broad learning system , minimum class variance BLS , extracted spectral–spatial features , data structures , feature extraction , spectral–spatial feature learning , learning (artificial intelligence) , spectral–spatial representation , classification performance model , generalisation ability , MCVBLS methods , intraclass distribution structure , global data structure , image classification , machine learning method , interclass discriminant information , global discriminative structure information , hyperspectral imaging , hyperspectral image classification
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Datenquelle:
Inhaltsverzeichnis – Band 14, Ausgabe 13
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