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dc.date.accessioned 2012-11-09T13:16:16Z
dc.date.available 2012-11-09T13:16:16Z
dc.date.issued 2006-08
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/23948
dc.description.abstract The Limited Receptive Area (LIRA) neural classifier is proposed for texture recognition of mechanically treated metal surfaces. It can be used in systems that have to recognize position and orientation of complex work pieces in the task of assembly of micromechanical devices. The performance of the proposed classifier was tested on specially created image database in recognition of four texture types that correspond to metal surfaces after:milling, polishing with sandpaper, turning with lathe and polishing with file. The promising recognition rate of 99.7% was obtained en
dc.language en es
dc.subject Object recognition es
dc.subject Scene Analysis es
dc.title Limited receptive area neural classifier for texture recognition of metal surfaces en
dc.type Objeto de conferencia es
sedici.identifier.isbn 0-387-34654-6 es
sedici.creator.person Martín, Anabel es
sedici.creator.person Baidyk, Tatiana es
sedici.creator.person Makeyev, Oleksandr es
sedici.description.note IFIP International Conference on Artificial Intelligence in Theory and Practice - Machine Vision es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Red de Universidades con Carreras en Informática (RedUNCI) es
sedici.subtype Objeto de conferencia es
sedici.rights.license Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
sedici.rights.uri http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
sedici.date.exposure 2006-08
sedici.relation.event 19 th IFIP World Computer Congress - WCC 2006 es
sedici.description.peerReview peer-review es


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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)