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Recognition of 3-D similar objects by GRNN

dc.contributor.authorPolat, Ovunc
dc.contributor.authorYildirim, Tulay
dc.contributor.institutionauthorYILDIRIM, Tülay
dc.date.accessioned2026-06-27T13:01:14Z
dc.date.issued2006
dc.description.abstractThis paper presents an approach for the recognition of similar objects automatically. In the recognition system, colour features were extracted from two dimensional (2-D) pose images of every 3-D object given and the classification of the objects was realized by using these feature vectors in General Regression Neural Networks-GRNN. The system has been simulated with eight different objects having similar shapes and high recognition rate was obtained. The ability of recognizing many undefined objects after training with low number of samples is important property of this system.en
dc.identifier.endpage+
dc.identifier.isbn978-1-4244-0238-0
dc.identifier.startpage145
dc.identifier.urihttps://hdl.handle.net/20.500.14981/49075
dc.identifier.wos000245347800037
dc.language.isotur
dc.publisherIEEE
dc.relation.conferenceIEEE 14th Signal Processing and Communications Applications
dc.relation.ispartof2006 IEEE 14TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS, VOLS 1 AND 2
dc.subjectComputer Science
dc.subjectEngineering
dc.subjectImaging Science & Photographic Technology
dc.titleRecognition of 3-D similar objects by GRNN
dc.typeProceedings Paper
dspace.entity.typePublication
local.import.sourceWOS

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