Strategies for combining classifiers using shared and distinct representations.

Kittler, J. and Hojjatoleslami, A. and Windeatt, T. (1997) Strategies for combining classifiers using shared and distinct representations. Pattern recognition letters, 18 (11-13). pp. 1373-1377. ISSN 0167-8655.

The full text of this publication is not available from this repository. (Contact us about this Publication)

Abstract

The problem of combining multiple classifiers which employ mixed mode representations consisting of some shared and some distinct features is studied. Two combination strategies are developed and experimentally compared on mammographic data to demonstrate their effectiveness.

Item Type:	Article
Uncontrolled keywords:	Classification; Multiple expert function
Subjects:	Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics Q Science > QA Mathematics (inc Computing science) > QA273 Probabilities Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, > QA76.76.E95 Expert Systems (Intelligent Knowledge Based Systems)
Divisions:	Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science > Applied Mathematics Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science > Statistics Faculties > Science Technology and Medical Studies > School of Engineering and Digital Arts > Image and Information Engineering Faculties > Science Technology and Medical Studies > School of Biosciences > Biomedical Research Group Faculties > Science Technology and Medical Studies > School of Computing > Theoretical Computing Group
Depositing User:	Sayed Ali Hojjatoleslami
Date Deposited:	19 May 2011 11:54
Last Modified:	19 May 2011 11:54
Resource URI:	http://kar.kent.ac.uk/id/eprint/27608 (The current URI for this page, for reference purposes)

• Depositors only (login required):