Semi-supervised probabilistic relaxation for image segmentation
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Otros documentos de la autoría: Martínez Usó, Adolfo; Martínez Sotoca, José; Pla, Filiberto; Anaya Sánchez, Henry
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Título
Semi-supervised probabilistic relaxation for image segmentationFecha de publicación
2011Editor
Springer-VerlagISSN
0302-9743Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
http://www.springerlink.com/content/7665350437031u83/fulltext.pdfPalabras clave / Materias
Resumen
In this paper, a semi-supervised approach based on probabilistic relaxation theory is presented. Focused on image segmentation, the presented technique combines two desirable properties; a very small number of labelled ... [+]
In this paper, a semi-supervised approach based on probabilistic relaxation theory is presented. Focused on image segmentation, the presented technique combines two desirable properties; a very small number of labelled samples is needed and the assignment of labels is consistently performed according
to our contextual information constraints. Our proposal has been tested on medical images from a dermatology application with quite promising preliminary
results. Not only the unsupervised accuracies have been improved as expected
but similar accuracies to other semi-supervised approach have been obtained using a considerably reduced number of labelled samples. Results have been also
compared with other powerful and well-known unsupervised image segmentation
techniques, improving significantly their results [-]
Publicado en
Lecture notes in computer science (2011), vol. 6669, 428-435Derechos de acceso
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