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    Graphical object recognition using statistical language models


    Keyes, Laura and O'Sullivan, Créidhe and Winstanley, Adam C. (2005) Graphical object recognition using statistical language models. In: Eighth International Conference on Document Analysis and Recognition, 2005. Proceedings. IEEE, pp. 1095-1099. ISBN 0769524206

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    Abstract

    This paper describes a proposed system for the recognition and labeling of graphical objects within architectural and engineering documents that integrates statistical language models (SLMs) with traditional classifiers. SLMs are techniques used with success in natural language processing (NLP) for use in such tasks as speech recognition and information retrieval. This research proposes the adaptation of SLMs for use with graphical notation i.e. statistical graphical language model (SGLMs). Reasoning of the similarities between natural language and technical graphics is presented and the proposed use of SGLM for graphical object recognition is described.

    Item Type: Book Section
    Keywords: statistical graphical language model; graphical object recognition; statistical language models; architectural documents; engineering documents; natural language processing; speech recognition; information retrieval;
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Item ID: 8104
    Identification Number: https://doi.org/10.1109/ICDAR.2005.120
    Depositing User: Dr. Adam Winstanley
    Date Deposited: 30 Mar 2017 14:31
    Publisher: IEEE
    Refereed: Yes
    URI:

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