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A cost-effective semisupervised classifier approach with kernels / M. Murat Dundar in IEEE Transactions on geoscience and remote sensing, vol 42 n° 1 (January 2004)

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 42 n° 1 (January 2004) . - pp 264 - 270 Titre : A cost-effective semisupervised classifier approach with kernels Type de document : Article/Communication Auteurs : M. Murat Dundar, Auteur ; D.L. Landgrebe, Auteur Année de publication : 2004 Article en page(s) : pp 264 - 270 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes descripteurs IGN] classificateur [Termes descripteurs IGN] classification semi-dirigée [Termes descripteurs IGN] distribution de Fisher [Termes descripteurs IGN] échantillon [Termes descripteurs IGN] itération [Termes descripteurs IGN] méthode fondée sur le noyau Résumé : (Auteur) In this paper, we propose a cost-effective iterative semisupervised classifier based on a kernel concept. The proposed technique incorporates unlabeled data into the design of a binary classifier by introducing and optimizing a cost function in a feature space that maximizes the Rayleigh coefficient while minimizing the total cost associated with misclassified labeled samples. The cost assigned to misclassified labeled samples accounts for the number of misclassified labeled samples as well as the amount by which they are on the wrong side of the boundary, and this counterbalances any potential adverse effect of unlabeled data on the classifier performance. Several experiments performed with remotely sensed data demonstrate that using the proposed semisupervised classifier shows considerable improvements over the supervised-only counterpart. Numéro de notice : A2004-046 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26574 [article]

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