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Exploring synergetic effects of dimensionality reduction and resampling tools on hyperspectral imagery data classification
dc.contributor.author | Sánchez Garreta, Josep Salvador | |
dc.contributor.author | García, Vicente | |
dc.contributor.author | Mollineda, Ramón A. | |
dc.date.accessioned | 2012-06-07T09:02:49Z | |
dc.date.available | 2012-06-07T09:02:49Z | |
dc.date.issued | 2011 | |
dc.identifier.citation | Lecture notes in computer science (2011), vol. 6871, 511-523 | ca_CA |
dc.identifier.issn | 0302-9743 | |
dc.identifier.issn | 1611-3349 | |
dc.identifier.uri | http://hdl.handle.net/10234/41300 | |
dc.description.abstract | The present paper addresses the problem of the classification of hyperspectral images with multiple imbalanced classes and very high dimensionality. Class imbalance is handled by resampling the data set, whereas PCA and a supervised filter are applied to reduce the number of spectral bands. This is a preliminary study that pursues to investigate the benefits of combining several techniques to tackle the imbalance and the high dimensionality problems, and also to evaluate the order of application that leads to the best classification performance. Experimental results demonstrate the significance of using together these two preprocessing tools to improve the performance of hyperspectral imagery classification. Although it seems that the most effective order corresponds to first a resampling strategy and then a feature (or extraction) selection algorithm, this is a question that still needs a much more thorough investigation in the future | ca_CA |
dc.description.sponsorShip | This work has partially been supported by the Spanish Ministry of Education and Science under grants CSD2007–00018, AYA2008–05965–0596 and TIN2009–14205, the Fundació Caixa Castelló–Bancaixa under grant P1–1B2009–04, and the Generalitat Valenciana under grant PROMETEO/2010/028 | ca_CA |
dc.format.extent | 13 p. | ca_CA |
dc.format.mimetype | application/pdf | ca_CA |
dc.language.iso | eng | ca_CA |
dc.publisher | Springer | ca_CA |
dc.relation.isFormatOf | The original publication is available at http://www.springerlink.com/content/jj6jn47540w31287/ | ca_CA |
dc.rights | © Springer-Verlag Berlin Heidelberg 2011 | ca_CA |
dc.rights.uri | http://www.springer.com/open+access/authors+rights?SGWID=0-176704-12-683201-0 | |
dc.subject | Synergetic effects | ca_CA |
dc.subject | Classification | ca_CA |
dc.subject | Hyperspectral images | ca_CA |
dc.subject | Multiple imbalanced clases | ca_CA |
dc.subject | Very high dimensionality | ca_CA |
dc.title | Exploring synergetic effects of dimensionality reduction and resampling tools on hyperspectral imagery data classification | ca_CA |
dc.type | info:eu-repo/semantics/article | ca_CA |
dc.identifier.doi | http://dx.doi.org/10.1007/978-3-642-23199-5_38 | |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | ca_CA |
dc.type.version | info:eu-repo/semantics/submittedVersion |
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