An evaluation of multi-expert configurations for the recognition of handwritten numerals

Rahman, A.F.R. and Fairhurst, M.C. (1998) An evaluation of multi-expert configurations for the recognition of handwritten numerals. Pattern Recognition, 31 (9). pp. 1255-1273. ISSN 0031-3203. (The full text of this publication is not available from this repository)

The full text of this publication is not available from this repository. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.1016/S0031-3203(97)00161-1

Abstract

In recent years, combination of multiple experts has become a major area of interest in designing practical and robust handwritten character recognition systems. Instead of building a single sophisticated and complicated classifier which is capable to handling all the various types of variations that are present in the handwritten character set, it has proved more prudent to apply relatively simpler classifiers (experts) by formulating ways of combining their individual decisions in order to generate robust and confident decisions. This paper presents a new class of decision combination approaches and compares the effectiveness of these approaches in successfully combining decisions by multiple experts in the specific application of hand written numeral recognition. Although the proposed approaches have been applied to a specific task of handwritten numeral recognition, the underlying concepts are completely generalised and should be applicable to a very broad task domain.

Item Type: Article
Uncontrolled keywords: Handwriting analysis; Numeral recognition; Multiple-expert classifiers; Hierarchical structures
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science
Q Science > Q Science (General) > Q335 Artificial intelligence
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics (see also: telecommunications)
Divisions: Faculties > Science Technology and Medical Studies > School of Engineering and Digital Arts
Depositing User: Tara Puri
Date Deposited: 07 Jul 2009 11:51
Last Modified: 07 Jul 2009 11:51
Resource URI: http://kar.kent.ac.uk/id/eprint/17002 (The current URI for this page, for reference purposes)
  • Depositors only (login required):