Dr. Vijendra Singh

Associate Professor
Mody University of Science and Technology, India

Highest Degree
Ph.D. in Engineering from Birla Institute of Technology, India

My URL
https://livedna.org/91.6684

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Biography

Dr. Vijendra Singh is currently working as Faculty member at Mody University of Science and Technology, India. He obtained his Ph.D. in Engineering from Birla Institute of Technology, India. His main area of interest related to Computer Science. His area of expertise includes Pattern Recognition, Image Processing, Feature Selection, Data Mining, Machine Learning, Outlier, Evolutionary Computation, Big Data, Neural Networks, and Data Science. He has published 10 articles in refereed journals, and 11 papers in national and international conferences, and 1 book contributed as author/co-author.

Area of Interest:

Computer Sciences
Pattern Recognition
Data Mining
Evolutionary Computation
Neural Networks

Selected Publications

  1. Vijendra, S. and S. Laxman, 2014. Multi objective line symmetry based evolutionary clustering approach. Soft Comput. Tech. Eng. Appl., 543: 49-58.
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  2. Vijendra, S. and S. Laxman, 2014. Effective evolution of clusters: a genetic clustering approach. Res. J. Inf. Technol., 6: 81-100.
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  3. Trikha, P. and S. Vijendra, 2013. Fast density based clustering algorithm. Int. J. Mach. Learn. Comput., 3: 10-12.
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  4. Vijendra, S., K. Ashiwini and S. Laxman, 2012. A fast evolutionary algorithm for automatic evolution of clusters. Inform. Technol. J., 11: 1409-1417.
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  5. Vasudeva, N., H.J. Parashar and S. Vijendra, 2012. Offline character recognition system using artificial neural network. Int. J. Mach. Learn. Comput., 2: 449-452.
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  6. Vijendra, S., 2011. Efficient clustering for high dimensional data: Subspace based clustering and density based clustering. Inform. Technol. J., 10: 1092-1105.
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  7. Singh, V., L. Sahoo and A. Kelkar, 2011. Mining clusters in data sets of data mining: An effective algorithm. Int. J. Comput. Ther. Eng., 3: 171-177.
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  8. Singh, V. and P. Trikha, 2011. Density based algorithm with automatic parameters generation. Proceeding of the IEEE 3rd International Conference on Machine Learning and Computing, Feb. 26-28, Singapore, pp: 555-558.

  9. Vijendra, S., L. Sahoo and K. Ashwini, 2010. An effective clustering algorithm for data mining. Proceedings of the International Conference on Data Storage and Data Engineering, February 9-10, 2010, Bangalore, India, pp: 250-253.
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  10. Singh, V., L. Sahoo and A. Kelkar, 2010. Mining subspace clusters in high dimensional data. Int. J. Recent Trends Eng. Technol., 3: 118-122.
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  11. Singh, V., 2010. Mining subspaces from high dimensional data. Proceedings of National Conference on ICT: Theory Application and Practices, March 5-6, SPSU University Press, Udaipur, India, pp: 101-103.
Member since September, 2015