• DocumentCode
    3334700
  • Title

    Web-based search system of pattern recognition for the pattern of industrial components by an innovate technology

  • Author

    Fan, Kuo-Chin ; Hsiao, Sung-Jung ; Sung, Wen-Tsai

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Eng., Nat. Central Univ., Keelung, Taiwan
  • Volume
    1
  • fYear
    2002
  • fDate
    2002
  • Firstpage
    82
  • Abstract
    This work utilizes the pattern recognition (PR) technologies by Client-Server network structure into a web-based recognizing system. The system uses a recurrent neural network (RNN) with associative memory to perform the action of training and recognition. Client-end engineer is able to draw directly the shape of engineering components by the browser, and the recognition system will proceed with search for the component database of company by the structure of Internet. In this paper, these component patterns are stored in the database system. Their properties and specifications are also attached to the data field of each component pattern except the pattern of engineering component. These Component patterns with the approach of database system will be able to improve the capacity of recognition system effectively. In our approach, the recognition system adopts parallel computing, and it will raise the recognition rate of system. Our recognition system is a client-server network structure by Internet. The last phase joins the technology of database matching in process of the recognition, and it will solve the problem of spurious state. In this paper, our study will be carried out in the Yang-Fen Automation Electrical Engineering Company. Therefore, the cooperative plan of above context will be analyzed and discussed in this paper.
  • Keywords
    client-server systems; content-addressable storage; engineering computing; image retrieval; pattern recognition; query processing; recurrent neural nets; associative memory; client-server network; component database; component patterns; database matching; engineering components; pattern recognition; recognition; recurrent neural network; training; Associative memory; Data engineering; Database systems; IP networks; Industrial training; Internet; Parallel processing; Pattern recognition; Recurrent neural networks; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Technology, 2002. IEEE ICIT '02. 2002 IEEE International Conference on
  • Print_ISBN
    0-7803-7657-9
  • Type

    conf

  • DOI
    10.1109/ICIT.2002.1189867
  • Filename
    1189867