A Comprehensive Study on Different Pattern Recognition Techniques

Navneet Kr. Kashyap*, B.K.Pandey**, Hardwari Lal Mandoria***, Ashok Kumar****
* PG Scholar, Department of Information Technology, G.B.P.U.A & T, Pantnagar, India.
**,**** Assistant Professor, Department of Information Technology, G.B.P.U.A & T, Pantnagar, India.
*** Professor and Head, Department of Information Technology, G.B.P.U.A & T, Pantnagar, India.
Periodicity:December - February'2016
DOI : https://doi.org/10.26634/jpr.2.4.5947

Abstract

Pattern Acceptance has been admired because of its advancement in the appliance areas. The applying breadth includes medicine, communications, automation, aggressive intelligence, abstracts mining, bioinformatics, certificate classification, accent recognition, business and abounding others. In this analysis, cardboard assorted approaches of Arrangement Acceptance has been presented with their pros-cons, and the appliance specific archetype has been confirmed. From the base of the survey, arrangement acceptance techniques could be categorized into six parts. Such awning techniques include Neural Network scheme, Statistics Techniques, Template Matching, Hybrid versions and Fuzzy Model.

Keywords

Statistical & Structural Pattern Recognition, Pattern Recognition Techniques, Pattern Recognition, Fuzzy Model, Neural Network Scheme, Hybrid Versions.

How to Cite this Article?

Kashyap, N. K., Pandey, B. K., Mandoria, H. L., and Kumar, A. (2016). A Comprehensive Study on Different Pattern Recognition Techniques. i-manager’s Journal on Pattern Recognition, 2(4), 42-49. https://doi.org/10.26634/jpr.2.4.5947

References

[1]. H.M. Abbas and M.M. Fahmy, (1994). “Neural Networks for Maximum Likelihood Clustering”. Signal Processing, Vol.36, No.1, pp.111-126.
[2]. H. Akaike, (1974). “A New Look at Statistical Model Identification”. IEEE Trans. Automatic Control, Vol.19, pp.716-723.
[3]. S. Amari, T.P. Chen, and A. Cichocki, (1997). “Stability Analysis of Learning Algorithms for Blind Source Separation”. Neural Networks, Vol.10, No.8, pp.1,345- 1,351.
[4]. A. Antos, L. Devroye, and L. Gyorfi, (1999). “Lower Bounds for Bayes Error Estimation”. IEEE Trans. Pattern Analysis and Machine Intelligence, Vol.21, No.7, pp.643- 645.
[6]. C.M. Bishop, (1995). Neural Networks for Pattern Recognition. Oxford: Clarendon Press.
[7]. C.J.C. Burges, (1998). “A Tutorial on Support Vector Machines for Pattern Recognition”. Data Mining and Knowledge Discovery, Vol.2, No.2, pp.121-167.
[8]. B. Cheng and D.M. Titterington, (1994). “Neural Networks: A Review from Statistical Perspective”. Statistical Science, Vol.9, No.1, pp.2-54.
[9]. P.A. Chou, (1991). “Optimal Partitioning for Classification and Regression Trees”. IEEE Trans. Pattern Analysis and Machine Intelligence, Vol.13, No.4, pp.340- 354.
[10]. T.M. Cover, (1992). “Geometrical and Statistical Properties of Systems of Linear Inequalities with Applications in Pattern Recognition”. IEEE Trans. Electronic Computers, Vol.14, pp.326-334.
[11]. P.A. Devijver and J. Kittler, (1989). Pattern Recognition: A Statistical Approach. London: Prentice Hall.
[12]. L. Devroye, (1988). “Automatic Pattern Recognition: A Study of the Probability of Error”. IEEE Trans. Pattern Analysis and Machine Intelligence, Vol.10, No.4, pp.530- 543.
[13]. U. Fayyad, G. Piatetsky-Shapiro, and P. Smyth, (1999). “Knowledge Discovery and Data Mining: Towards a Unifying Framework”. Proc. Second Int'l Conf. Knowledge Discovery and Data Mining.
[14]. Anil K Jain, Robert P.W. Duin and Jianchang Mao, (2000). “Statistical Pattern Recognition: A review”. IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol.22, No.1, pp.4-37.
[15]. Scott C Newton, Surya Pemmaraju and Sunanda Mitra, (1992). “Adaptive Fuzzy Leader Clustering of Complex Data Sets in Pattern recognition”. IEEE Transactions on Neural Network, Vol.3, No.5, pp.794-800.
[16]. Jenn- Hwai Yang and Miin Shen Yang, (2005). “A Control Chart Pattern Recognition System Using Statistical Correlation Coefficient Method”. Computers and Industrial Engineering, Vol.48, pp.205-221.
[17]. Jun Hai Zhai, (2006). “An Overview of Pattern th Classification Methodologies”. Proceedings of 5 International Conference on Machine Learning and Cybernetics, pp.3222-3227.
[18]. Liu, J., Sun, J. And Wang, S. (2006). “Pattern Recognition: An overview”. International Journal of Computer Science and Network Security (IJCSNS), Vol.6, No.6.
[19]. Vapnik, V., (2010). The Nature of Statistical Learning Theory. Springer.
[20]. Robert Jain, and Mao, (2000). “Statistical pattern recognition: A Review”. IEEE Transaction on Machine Learning and Pattern Analysis, Vol.22, No.1.
[21]. Wikipedia. Introduction to pattern recognition.
[22]. Thomas Minka. A Statistical Learning/Pattern Recognition.
[23]. Zheng, He, (2011). Classification Technique in Pattern Recognition, University of Technology, Sydney, ISBN 80-903100-8-7, WSCG.
[24]. Seema Asht, and Rajeshwar Dass, (2012). “Pattern Recognition Techniques: A Review”. International Journal of Computer Science and Telecommunications.
[25]. M. Parasher, S. Sharma, A.K Sharma, and J.P Gupta, (2011). “Anatomy on Pattern Recognition”. Indian Journal of Computer Science and Engineering (IJCSE), Vol.2, No.3.
[26]. Amin Fazel and Shantnu Chakrabartty, (1996). “An Overview of Statistical Pattern Recognition Techniques for Speaker Verification”. IEEE Circuits and Systems, pp.61-81.
[27]. K.S. Fu, (1982). Syntactic Pattern Recognition and Applications. Englewood Cliffs, N.J.: Prentice-Hall.
[28]. K. Tumer and J. Ghosh, (1996). "Analysis of Decision Boundaries in Linearly Combined Neural Classifiers". Pattern Recognition, Vol.29, pp.341-348.
[29]. R.O.Duda and P.E.Hart, (1973). Pattern Classification and Scene, Analysis, New York: John Wiley & sons.
[30]. Majida Ali Abed, Ahmad Nasser Ismail and ZubadiMatiz Hazi, (June, 2010). “Pattern recognition Using Genetic Algorithm”. International Journal of Computer and Electrical Engineering, Vol.2, No.3.
[31]. Mohammad S. Alam, and Mohammad A. Karim, (2004). “Advances in Pattern Recognition Algorithms, Architectures and Devices”. Optical Engineering, Vol.43, No.8.
[32]. B. Ripley, (1993). Statistical Aspects of Neural Networks, Networks on Chaos: Statistical and Probabilistic Aspects. U. Bornndorff-Nielsen, J.Jensen, and W. Kendal, Eds., Chapman and Hall.
[33]. J. Anderson, A. Pellionisz, and E. Rosenfeld, (1990). Neuro Computing 2: Directions for Research. Cambridge Mass.: MIT Press.
[34]. T. Pavlidis and F. Ali, (1975). "Computer Recognition of Handwritten Numerals by Polygonal Approximations”. IEEE Trans. Syst.,Man,Cybern. Vol. SMC-5.
[35]. Anupam Joshi, Narendram Ramakrishman, Elias N. Houstis and John R. Rice, (1997). "On Neurobiological, Neuro-Fuzzy, Machine Learning And Statistical Pattern Recognition Techniques". IEEE Trans. on Neural Networks, Vol.8, No.1.
[36]. J.C. Bezdek, (1981). Pattern Recognition with Fuzzy Objective Function Algorithm, New York: Plenum Press.
[37]. R. O. Duda, P. E. Hart and D. G. Stork, (2000). Pattern Classification, John Wiley & Sons.
[38]. B. Ripley, (1996). Pattern Recognition and Neural Networks, Cambridge University Press, Cambridge.
[39]. Sergios Theodoridis, and Konstantinos Koutroumbas, (1982). “Pattern recognition”. Pattern Recognition, Elsevier, USA.
[40]. Anil k Jain, and Robert P.W Duin, (2004). Introduction To Pattern Recognition. The Oxford Companion to the Mind, Second Edition, Oxford University Press, Oxford, UK, pp.698- 703.
[41]. S.P. Shinde and V.P. Deshmukh, (2011). “Implementation of Pattern Recognition Techniques and Overview of its Applications in various areas of Artificial Intelligence”. International Journal of Advances in Engineering & Technology, Vol.1, No.4, pp.127-137.
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