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:	http://ieeexplore.ieee.org
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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