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Mathematical Problems in Engineering
Volume 2017, Article ID 6204742, 18 pages
https://doi.org/10.1155/2017/6204742
Research Article

Indian Classical Dance Classification with Adaboost Multiclass Classifier on Multifeature Fusion

Department of Electronics and Communications Engineering, KL University, Green Fields, Vaddeswaram, Guntur, Andhra Pradesh, India

Correspondence should be addressed to P. V. V. Kishore; ni.ytisrevinulk@erohsikvvp

Received 1 June 2017; Revised 27 July 2017; Accepted 17 August 2017; Published 26 September 2017

Academic Editor: Daniel Zaldivar

Copyright © 2017 K. V. V. Kumar et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [3 citations]

The following is the list of published articles that have cited the current article.

  • K. V. V. Kumar, P. V. V. Kishore, D. Anil Kumar, and E. Kiran Kumar, “Indian classical dance action identification using adaboost multiclass classifier on multifeature fusion,” 2018 Conference on Signal Processing And Communication Engineering Systems (SPACES), pp. 167–170, . View at Publisher · View at Google Scholar
  • G. Anantha Rao, K. Syamala, P. V. V. Kishore, and A. S. C. S. Sastry, “Deep convolutional neural networks for sign language recognition,” 2018 Conference on Signal Processing And Communication Engineering Systems (SPACES), pp. 194–197, . View at Publisher · View at Google Scholar
  • P. V. V. Kishore, K. V. V. Kumar, E. Kiran Kumar, A. S. C. S. Sastry, M. Teja Kiran, D. Anil Kumar, and M. V. D. Prasad, “Indian Classical Dance Action Identification and Classification with Convolutional Neural Networks,” Advances in Multimedia, vol. 2018, pp. 1–10, 2018. View at Publisher · View at Google Scholar