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dc.contributor.authorChuang, JHen_US
dc.contributor.authorWang, PHen_US
dc.contributor.authorWu, MCen_US
dc.date.accessioned2014-12-08T15:46:24Z-
dc.date.available2014-12-08T15:46:24Z-
dc.date.issued1999-07-01en_US
dc.identifier.issn0360-8352en_US
dc.identifier.urihttp://hdl.handle.net/11536/31227-
dc.description.abstractThis paper presents a classification scheme for 3D block-shaped parts. A part is block-shaped if the contours of its orthographic projections are all rectangles, A block-shaped part is classified based on its partitioned view-contours, which are the result of partitioning the contours of its orthographic projections by visible or invisible projected line;segments. The regions and their adjacency in a partitioned view-contour are first converted to a graph, then to a reference tree, and finally to a vector form, with which a back-propagation neural network classifier can be trained and applied. The proposed back-propagation neural network classifier is in a cascaded structure and has advantages that each network can be limited to a small size and trained independently. Based on the classification results on their partitioned view-contours, parts are grouped into families that can be in one of the three levels of similarity. Extensive empirical tests have been performed; the pros and cons of the approach are also investigated. (C) 1999 Elsevier Science Ltd. All rights reserved.en_US
dc.language.isoen_USen_US
dc.subjectpart classificationen_US
dc.subjectblock-shaped partsen_US
dc.subjectneural networksen_US
dc.titleAutomatic classification of block-shaped parts based on their 2D projectionsen_US
dc.typeArticleen_US
dc.identifier.journalCOMPUTERS & INDUSTRIAL ENGINEERINGen_US
dc.citation.volume36en_US
dc.citation.issue3en_US
dc.citation.spage697en_US
dc.citation.epage718en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.department工業工程與管理學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.contributor.departmentDepartment of Industrial Engineering and Managementen_US
dc.identifier.wosnumberWOS:000083979300012-
dc.citation.woscount6-
Appears in Collections:Articles


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