Using the RNN to develop a Web-based pattern recognition system for pattern search of component database

Sung Jung Hsiao, Shih Ching Ou, Kuo Chin Fan, Wen Tsai Sung

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This study attempts to apply pattern recognition (PR) technologies with associative memory to real-time pattern recognition of engineering components using a client-server network structure in a Web-based recognition system. A remote engineer is able to draw directly the shape of engineering components using the browser, and the recognition system will search for the component database of a company using the Internet. Component patterns are stored in the database system. Their properties and specifications are also attached to the data field of each component pattern except that of engineering components. In our approach, the recognition system adopts parallel computing, and will raise the recognition rate. Our recognition system is a client-server network structure using the Internet. The system uses a recurrent neural network (RNN) with associative memory to perform training and recognition. The last phase utilizes the technology of database matching and solves the problem of spurious state. Our system will be used at the Yang-Fen Automation Electrical Engineering Company.

Original languageEnglish
Title of host publicationProceedings - 1st International Symposium on Cyber Worlds, CW 2002
EditorsShietung Peng, Shuichi Yukita, Vladimir V. Savchenko
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages146-153
Number of pages8
ISBN (Electronic)0769518621, 9780769518626
DOIs
StatePublished - 2002
Event1st International Symposium on Cyber Worlds, CW 2002 - Tokyo, Japan
Duration: 6 Nov 20028 Nov 2002

Publication series

NameProceedings - 1st International Symposium on Cyber Worlds, CW 2002

Conference

Conference1st International Symposium on Cyber Worlds, CW 2002
Country/TerritoryJapan
CityTokyo
Period6/11/028/11/02

Keywords

  • Pattern Recognition
  • RNN
  • Web-Based
  • Web-Based
  • component database
  • engineering components

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