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Hyperspectral Classification Based on Texture Feature Enhancement and Deep Belief Networks

Hyperspectral Classification Based on Texture Feature Enhancement and Deep Belief Networks

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_19e59f42b35b485ebd235bc439fb1619

Hyperspectral Classification Based on Texture Feature Enhancement and Deep Belief Networks

About this item

Full title

Hyperspectral Classification Based on Texture Feature Enhancement and Deep Belief Networks

Publisher

MDPI AG

Journal title

Remote sensing (Basel, Switzerland), 2018-03, Vol.10 (3), p.396

Language

English

Formats

Publication information

Publisher

MDPI AG

More information

Scope and Contents

Contents

With success of Deep Belief Networks (DBNs) in computer vision, DBN has attracted great attention in hyperspectral classification. Many deep learning based algorithms have been focused on deep feature extraction for classification improvement. Multi-features, such as texture feature, are widely utilized in classification process to enhance classifi...

Alternative Titles

Full title

Hyperspectral Classification Based on Texture Feature Enhancement and Deep Belief Networks

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_19e59f42b35b485ebd235bc439fb1619

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_19e59f42b35b485ebd235bc439fb1619

Other Identifiers

ISSN

2072-4292

E-ISSN

2072-4292

DOI

10.3390/rs10030396

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