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

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 compone...

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Bibliographic Details
Main Authors: Sung-Jung Hsiao, Shih-Ching Ou, Kuo-Chin Fan, Wen-Tsai Sung
Format: Conference Proceeding
Language:English
Subjects:
Associative memory
Data engineering
Database systems
Internet
Parallel processing
Pattern recognition
Real time systems
Recurrent neural networks
Shape
Systems engineering and theory
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Summary: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.
DOI:10.1109/CW.2002.1180873