Volume 7, Issue 4 (December 2011)                   IJEEE 2011, 7(4): 217-224 | Back to browse issues page

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Ebrahimpour R, Sarhangi S, Sharifizadeh F. Mixture of Experts for Persian handwritten word recognition. IJEEE 2011; 7 (4) :217-224
URL: http://ijeee.iust.ac.ir/article-1-332-en.html
Mixture of Experts for Persian handwritten word recognition
R. Ebrahimpour , S. Sarhangi , F. Sharifizadeh
Abstract:   (6753 Views)
This paper presents the results of Persian handwritten word recognition based on Mixture of Experts technique. In the basic form of ME the problem space is automatically divided into several subspaces for the experts, and the outputs of experts are combined by a gating network. In our proposed model, we used Mixture of Experts Multi Layered Perceptrons with Momentum term, in the classification Phase. We produce three different Mixture of Experts structure. Experimental result for proposed method show an error rate reduction of 6.42 % compare to the mixture of MLPs experts. Comparison with some of the most related methods indicates that the proposed model yields excellent recognition rate in handwritten word recognition.
Keywords: Mixture of Experts , Persian Handwritten Word Recognition , Neural Network Ensembles , OCR
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Type of Study: Research Paper | Subject: Hybrid Systems Analysis and Design
Received: 2010/10/20 | Revised: 2011/12/24 | Accepted: 2011/12/19
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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
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© 2022 by the authors. Licensee IUST, Tehran, Iran. This is an open access journal distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.