Web-based distributed pattern recognition system

Sung Jung Hsiao, Wen Tsai Sung, Kuo Chin Fan

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

3 Scopus citations


This study attempts to apply the principle of neural networks and pattern recognition (PR) technologies to real-time recognition by client-server network structure into a web-based recognizing system. In this paper, we recommend a Web-Based PR technology, which is improved recurrent neural network (RNN) from possessing feedback and non-linear activation function with its input, be taken out threshold. The purpose of this article is. to construct a Client-Server network structure for PR system with associative memory. The Server-end is built a databases management system for storage sample patterns. In proceed with training, the user can real-time assign any pattern, which is a record in the Server-end databases. In deal with retrieve task, we propose a novel PR method via databases matching, it can efficient solve spurious states problem from RNN in the WBPR system. On the other hand, taking advantage of Database Matching is to overcome the capacity restrictions on RNN. In order to clarify and corroborate the above Web-Based PR technology, thus a simulation experiment will be presented and their algorithms are also discussed.

Original languageEnglish
Title of host publicationProceedings - 6th International Conference on Information Visualisation, IV 2002
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages8
ISBN (Electronic)0769516564
StatePublished - 2002
Event6th International Conference on Information Visualisation, IV 2002 - London, United Kingdom
Duration: 10 Jul 200212 Jul 2002

Publication series

NameProceedings of the International Conference on Information Visualisation
ISSN (Print)1093-9547


Conference6th International Conference on Information Visualisation, IV 2002
Country/TerritoryUnited Kingdom


  • Associative memory
  • Automation
  • Character recognition
  • Computer science
  • Databases
  • Internet
  • Neural networks
  • Pattern recognition
  • Real time systems
  • Recurrent neural networks


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