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Article: A neural network system for two-dimensional feature recognition
Title | A neural network system for two-dimensional feature recognition |
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Authors | |
Issue Date | 1998 |
Publisher | Taylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/0951192X.asp |
Citation | International Journal Of Computer Integrated Manufacturing, 1998, v. 11 n. 2, p. 111-117 How to Cite? |
Abstract | Recognition of geometric features is important for automatic evaluation of part designs and development of process plans. This paper describes an implementation of a neural network for feature recognition in sheet metal parts created in a CAD system. One major part of the implementation is the development of a rotation- and translation-insensitive encoding scheme which extracts critical information from geometric features and candidate geometric loops. The successful implementation has led to a powerful system where end users can customize the domain of features that can be recognized. Training of the neural network memory is also achieved through a user-friendly graphic interface. ©1998 Taylor & Francis Ltd. |
Persistent Identifier | http://hdl.handle.net/10722/156296 |
ISSN | 2023 Impact Factor: 3.7 2023 SCImago Journal Rankings: 0.987 |
ISI Accession Number ID | |
References |
DC Field | Value | Language |
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dc.contributor.author | Chen, YH | en_US |
dc.contributor.author | Lee, HM | en_US |
dc.date.accessioned | 2012-08-08T08:41:52Z | - |
dc.date.available | 2012-08-08T08:41:52Z | - |
dc.date.issued | 1998 | en_US |
dc.identifier.citation | International Journal Of Computer Integrated Manufacturing, 1998, v. 11 n. 2, p. 111-117 | en_US |
dc.identifier.issn | 0951-192X | en_US |
dc.identifier.uri | http://hdl.handle.net/10722/156296 | - |
dc.description.abstract | Recognition of geometric features is important for automatic evaluation of part designs and development of process plans. This paper describes an implementation of a neural network for feature recognition in sheet metal parts created in a CAD system. One major part of the implementation is the development of a rotation- and translation-insensitive encoding scheme which extracts critical information from geometric features and candidate geometric loops. The successful implementation has led to a powerful system where end users can customize the domain of features that can be recognized. Training of the neural network memory is also achieved through a user-friendly graphic interface. ©1998 Taylor & Francis Ltd. | en_US |
dc.language | eng | en_US |
dc.publisher | Taylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/0951192X.asp | en_US |
dc.relation.ispartof | International Journal of Computer Integrated Manufacturing | en_US |
dc.title | A neural network system for two-dimensional feature recognition | en_US |
dc.type | Article | en_US |
dc.identifier.email | Chen, YH:yhchen@hkucc.hku.hk | en_US |
dc.identifier.authority | Chen, YH=rp00099 | en_US |
dc.description.nature | link_to_subscribed_fulltext | en_US |
dc.identifier.scopus | eid_2-s2.0-0000863719 | en_US |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-0000863719&selection=ref&src=s&origin=recordpage | en_US |
dc.identifier.volume | 11 | en_US |
dc.identifier.issue | 2 | en_US |
dc.identifier.spage | 111 | en_US |
dc.identifier.epage | 117 | en_US |
dc.identifier.isi | WOS:000071791000003 | - |
dc.publisher.place | United Kingdom | en_US |
dc.identifier.scopusauthorid | Chen, YH=7601430448 | en_US |
dc.identifier.scopusauthorid | Lee, HM=8454962200 | en_US |
dc.identifier.issnl | 0951-192X | - |