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Erschienen in:
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2017 | OriginalPaper | Buchkapitel

1. Introduction

verfasst von : Arindam Chaudhuri, Krupa Mandaviya, Pratixa Badelia, Soumya K. Ghosh

Erschienen in: Optical Character Recognition Systems for Different Languages with Soft Computing

Verlag: Springer International Publishing

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Abstract

Optical character recognition (OCR) is one of the most popular areas of research in pattern recognition [3, 25] since past few decades. It is an actively studied topic in industry and academia [8, 15, 18, 24] because of its immense application potential. OCR was initially studied in early 1930s [23].

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Nächstes Kapitel Optical Character Recognition Systems
Literatur
1.
Berg, J. Van Den, Bergh, W. M. Van Den, Kaymak, U., Probabilistic and Statistical Fuzzy Set Foundations of Competitive Exception Learning, ERIM Report Series Research in Management, 2001.
2.
Buckley, J. J., Fuzzy Probability and Statistics, Studies in Fuzziness and Soft Computing, Springer Verlag, 2006.
3.
Bunke, H., Wang, P. S. P. (Editors), Handbook of Character Recognition and Document Image Analysis, World Scientific, 1997.
4.
Chaudhuri, A., Ghosh, S. K., Sentiment Analysis of Customer Reviews Using Robust Hierarchical Bidirectional Recurrent Neural Network, Book Chapter: Artificial Intelligence Perspectives in Intelligent Systems, Radek Silhavy, Roman Senkerik, Zuzana Kominkova Oplatkova, Petr Silhavy, Zdenka Prokopova, (Editors), Advances in Intelligent Systems and Computing, Springer International Publishing, Switzerland, Volume 464, pp 249–261, 2016.
5.
Chaudhuri, A., Fuzzy Rough Support Vector Machine for Data Classification, International Journal of Fuzzy System Applications, 5(2), pp 26–53, 2016.
6.
Chaudhuri, A., Modified Fuzzy Support Vector Machine for Credit Approval Classification, AI Communications, 27(2), pp 189–211, 2014.
7.
Chaudhuri, A., De, Fuzzy Support Vector Machine for Bankruptcy Prediction, Applied Soft Computing, 11(2), pp 2472–2486, 2011.
8.
Chaudhuri, A., Some Experiments on Optical Character Recognition Systems for different Languages using Soft Computing Techniques, Technical Report, Birla Institute of Technology Mesra, Patna Campus, India, 2010.
9.
Chaudhuri, A., De, K., Job Scheduling using Rough Fuzzy Multi-Layer Perception Networks, Journal of Artificial Intelligence: Theory and Applications, 1(1), pp 4–19, 2010.
10.
Chaudhuri, A., De, K., Chatterjee, D., Discovering Stock Price Prediction Rules of Bombay Stock Exchange using Rough Fuzzy Multi-Layer Perception Networks, Book Chapter: Forecasting Financial Markets in India, Rudra P. Pradhan, Indian Institute of Technology Kharagpur, (Editor), Allied Publishers, India, pp 69–96, 2009.
11.
Haykin, S., Neural Networks and Learning Machines, 3rd Edition, Prentice Hall, 2008.
12.
Jang, J. S. R., Sun, C. T., Mizutani, E., Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence, Prentice Hall, 1997.
13.
Kosko, B., Neural Networks and Fuzzy Systems: A Dynamical Systems Approach to Machine Intelligence, Prentice Hall of India, 2008.
14.
Kreyszig, E., Advanced Engineering Mathematics, 10th Edition, Wiley International Press, 2010.
15.
Leondes, C. T., Image Processing and Pattern Recognition, 1st Edition, Elsevier, 1997.
16.
Liu, H, Motoda, H., Feature Extraction, Construction and Selection: A Data Mining Perspective, Kluwer Academic, 1998.
17.
Mitchell, M., An Introduction to Genetic Algorithms, MIT Press, 1998.
18.
Mollah, A. F., Majumder, N., Basu, S., Nasipuri, M., Design of an Optical Character Recognition System for Camera based Handheld Devices, International Journal of Computer Science Issues, 8 (4), pp 283–289, 2011.
19.
Padhy, N. P., Simon, S. P., Soft Computing: With MATLAB Programming, Oxford University Press, 2015.
20.
Pal, S. K, Mitra, S., Mitra, P., Rough Fuzzy MLP: Modular Evolution, Rule Generation and Evaluation, IEEE Transactions on Knowledge and Data Engineering, 15 (1), pp 14–25, 2003.
21.
Polkowski, L, Rough Sets – Mathematical Foundations, Advances in Intelligent and Soft Computing, Springer Verlag, 2002.
22.
Pratihar, D. K., Soft Computing, Alpha Science International Limited, 2007.
23.
Rice, S. V., Nagy, G., Nartker, T. A., Optical Character Recognition: An Illustrated Guide to the Frontier, The Springer International Series in Engineering and Computer Science, Springer US, 1999.
24.
Yamasaki, I., Quantitative Evaluation of Print Quality for Optical Character Recognition Systems, IEEE Transactions on Systems, Man and Cybernetics, 8 (5), pp 371–381, 1978.
25.
Yu, F. T. S., Jutamulia, S. (Editors), Optical Pattern Recognition, Cambridge University Press, 1998.
26.
Zadeh, L. A., Fuzzy Logic, Neural Networks and Soft Computing, Communications of the ACM, 37(3), pp 77–84, 1994.
27.
Zadeh, L. A., Fuzzy Sets, Information and Control, 8(3), pp 338–353, 1965.
28.
Zeng, J., Liu, Z. Q., Type-2 Fuzzy Markov Random Fields and their Application to Handwritten Chinese Character Recognition, IEEE Transactions on Fuzzy Systems, 16(3), pp 747–760, 2008.
29.
Zill, D. G., Wright, W. S., Advanced Engineering Mathematics, 4th Edition, Jones and Bartlett Private Limited, 2011.
30.
Zimmermann, H. J., Fuzzy Set Theory and its Applications, 4th Edition, Kluwer Academic Publishers, Boston, 2001.
31.
32.
33.
34.
Metadaten
Titel
Introduction
verfasst von
Arindam Chaudhuri
Krupa Mandaviya
Pratixa Badelia
Soumya K. Ghosh
Copyright-Jahr
2017
Buch
Optical Character Recognition Systems for Different Languages with Soft Computing

Print ISBN: 978-3-319-50251-9

Electronic ISBN: 978-3-319-50252-6

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-3-319-50252-6_1

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