NDLI: Study of neural networks to improve performance for character recognition

Content Provider	IEEE Xplore Digital Library
Author	Gheorghita, S. Munteanu, R. Enache, M.
Copyright Year	2012
Description	Author affiliation: Faculties of Electrical Engineering, Technical University of Cluj-Napoca, Daicoviciu St., 15, 40020, Romania (Gheorghita, S.; Munteanu, R.) \|\| Dept. of Automation Technical University of Cluj-Napoca, Daicoviciu St., 15, 40020, Romania (Enache, M.)
Abstract	Three methods are proposed to improve the performance of a system based on feedforward neural networks, that is used for character recognition which are perturbed with noise up to 50%. Have been studied neural networks using backpropagation algorithm. The first element introduced in this study is to train the network in stages, using input data with noise, from 0 to 25% (steps 10,15,20,25) and then from 30% to 40% (steps 30,35,40). This approach has allowed fewer errors up to 1,2% for noise plateau 40%–50%. The second proposed method consists in introducing a vector of stability for the primary information, in stages of network training and then character recognition, with role to reduce the influence of noise on the input data. Stability vector proposed is a linear array with 5 constant parameters. The network used has 35 inputs, 16,20,25,30 or 50 nodes in the hidden layer and 26 outputs (one for each letter). The simulation and experimental results demonstrate that the proposed “vector of stability” can improve performance by decreasing the number of errors up to 1,7% for a neural network with 30 or 50 nodes in hidden layer. The third element proposed is to use reverse information (reverse the bits 0 with 1 and 1 with 0). Have been used two networks that process information. Then their outputs are analyzed and processed by a logic block. With this technique performances have been improved by decreasing the number of errors with 1%, 1.5% and 2.3% for 40%, 45% and 50% noise data.
Starting Page	323
Ending Page	326
File Size	235264
Page Count	4
File Format	PDF
ISBN	9781467307017
e-ISBN	9781467307048
DOI	10.1109/AQTR.2012.6237725
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-05-24
Publisher Place	Romania
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Noise Vectors Character recognition Newton method Biological neural networks
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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