[1] W. Y. Huang and R. P. Lippmann, ―Neural Net and Traditional Classifiers,‖ in Neural Information Processing Systems, 1988, pp. 387–396.

[2] V.N.Vapnik, ―The Nature of Statistical Learning Theory‖, Springer-Verlag, New York, 1995.

[3] C. J. C. Burges, ―A tutorial on support vector machines for pattern recognition‖, Data Mining and Knowledge Discovery, 2 (2), pp. 121–167, 1998.

[4] G. Shakhnarovich, T. Darrell, P. Indyk, ―Nearest neighbor methods in learning and vision: Theory and Practice,‖ MIT Press, 2005.

[5] M. Ghose, R. Pradhan, and S. Ghose, ―Decision tree classification of remotely sensed satellite data using spectral separability matrix,‖ International Journal of Advanced Computer Science and Applications, vol. 1, no. 5, pp. 93– 101, 2010.

[6] A. D. Kulkarni, Computer Vision and Fuzzy Neural Systems. Upper Saddle River, NJ: Prentice Hall,2001.

[7] Ankur Dixit, Shefali Agarwal, ―Comparison of Various Models and Optimum Range of its Parameters used in SVM Classification of Digital Satellite Image‖, Proceedings of the 2013 IEEE Second International Conference on Image Information Processing.

[8] Soumadip Ghosh, Sushanta Biswas, Debasree Sarkar and Partha Pratim Sarkar, ―A Tutorial on Different Classification Techniques for Remotely Sensed Imagery Datasets‖, Smart Computing Review, vol. 4, no. 1, February 2014.

[9] S.Manthira Moorthi, Indranil Misra, Rajdeep Kaur, Nikunj P Darji and R. Ramakrishnan, ―Kernel based learning approach for satellite image classification using support vector machine‖, 978-1-4244- 9477-4/11/$26.00 ©2011 IEEE.

[10] Wei WU, Guanglai GAO ―Remote Sensing Image Classification with Multiple Classifiers based on Support Vector Machines‖, 2012 Fifth International Symposium on Computational Intelligence and Design.

[11] Falah Chamasemani, Yashwant Prasad Singh, ―Multiclass Support Vector Machine (SVM) classifiers – An Application in Hypothyroid detection and Classification‖, 2011 Sixth International Conference on Bio-Inspired Computing: Theories and Applications.

[1] W. Y. Huang and R. P. Lippmann, ―Neural Net and Traditional Classifiers,‖ in Neural Information Processing Systems, 1988, pp. 387–396.

[2] V.N.Vapnik, ―The Nature of Statistical Learning Theory‖, Springer-Verlag, New York, 1995.

[3] C. J. C. Burges, ―A tutorial on support vector machines for pattern recognition‖, Data Mining and Knowledge Discovery, 2 (2), pp. 121–167, 1998.

[4] G. Shakhnarovich, T. Darrell, P. Indyk, ―Nearest neighbor methods in learning and vision: Theory and Practice,‖ MIT Press, 2005.

[5] M. Ghose, R. Pradhan, and S. Ghose, ―Decision tree classification of remotely sensed satellite data using spectral separability matrix,‖ International Journal of Advanced Computer Science and Applications, vol. 1, no. 5, pp. 93– 101, 2010.

[6] A. D. Kulkarni, Computer Vision and Fuzzy Neural Systems. Upper Saddle River, NJ: Prentice Hall,2001.

[7] Ankur Dixit, Shefali Agarwal, ―Comparison of Various Models and Optimum Range of its Parameters used in SVM Classification of Digital Satellite Image‖, Proceedings of the 2013 IEEE Second International Conference on Image Information Processing.

[8] Soumadip Ghosh, Sushanta Biswas, Debasree Sarkar and Partha Pratim Sarkar, ―A Tutorial on Different Classification Techniques for Remotely Sensed Imagery Datasets‖, Smart Computing Review, vol. 4, no. 1, February 2014.

[9] S.Manthira Moorthi, Indranil Misra, Rajdeep Kaur, Nikunj P Darji and R. Ramakrishnan, ―Kernel based learning approach for satellite image classification using support vector machine‖, 978-1-4244- 9477-4/11/$26.00 ©2011 IEEE.

[10] Wei WU, Guanglai GAO ―Remote Sensing Image Classification with Multiple Classifiers based on Support Vector Machines‖, 2012 Fifth International Symposium on Computational Intelligence and Design.

[11] Falah Chamasemani, Yashwant Prasad Singh, ―Multiclass Support Vector Machine (SVM) classifiers – An Application in Hypothyroid detection and Classification‖, 2011 Sixth International Conference on Bio-Inspired Computing: Theories and Applications.

[12] Ryad Malik, Radja Kheddam and Aichouche Belhadj-Aissa.," Object-Oriented SVM Classifier for ALSAT-2A High Spatial Resolution Imagery: A Case Study of Algiers Urban Area", 978-1-4799-8637-8/15/$31.00 ©2015 IEEE.

[13] M. Ghose, R. Pradhan, and S. Ghose, ―Decision tree classification of remotely sensed satellite data using spectral separability matrix,‖ International Journal of Advanced Computer Science and Applications, vol. 1, no. 5, pp. 93– 101, 2010.

[14] A. D. Kulkarni, Computer Vision and Fuzzy Neural Systems. Upper Saddle River, NJ: Prentice Hall, 2001.

[15] Y. Murali Mohan Babu, M.V. Subramanyam & M.N. Giriprasad, ―Fusion and Texture based Classification of Indian Microwave Data - A Comparative Study‖, International Journal of Applied Engineering Research, Volume 10, Issue 1, 1003-1010, February 2015.

[16] M.V. Subramanyam & M.N. Giriprasad, ―Fusion based land cover classification of Risat-1 data‖, in an International Conference on Industrial Electrical and Electronics and Electronics Engineering (ICIEEE), Bangkok, August 2014.