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Reconstructing persistent graph structures from noisy images

 

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dc.creator Chernov, Alexey es
dc.creator Kurlin, Vitaliy es
dc.date.accessioned 2015-07-02T07:21:48Z
dc.date.available 2015-07-02T07:21:48Z
dc.date.issued 2013 es
dc.identifier.issn 1885-4508 es
dc.identifier.uri http://hdl.handle.net/11441/26521
dc.description.abstract Let a point cloud be a noisy dotted image of a graph on the plane. We present a new fast algorithm for reconstructing the original graph from the given point cloud. Degrees of vertices in the graph are found by methods of persistent topology. Necessary parameters are automatically optimized by machine learning tools. es
dc.format application/pdf es
dc.language.iso eng es
dc.publisher Universidad de Sevilla es
dc.relation.ispartof Image-A : Applicable Mathematics in Image Engineering, 3 (5), 19-22 es
dc.rights Atribución-NoComercial-SinDerivadas 4.0 España es
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/ es
dc.subject Graph reconstruction es
dc.subject Noisy image es
dc.subject Point cloud data es
dc.subject Persistent topology es
dc.title Reconstructing persistent graph structures from noisy images es
dc.type info:eu-repo/semantics/article es
dc.type.version info:eu-repo/semantics/publishedVersion es
dc.rights.accessrights info:eu-repo/semantics/openAccess es
dc.relation.publisherversion http://institucional.us.es/revistas/imagen_a/5/art_4.pdf es
dc.identifier.idus https://idus.us.es/xmlui/handle/11441/26521
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