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Applied Computational Intelligence and Soft Computing
Volume 2016, Article ID 2796863, 17 pages
Research Article

A Study of Moment Based Features on Handwritten Digit Recognition

Department of Computer Science and Engineering, Jadavpur University, 188 Raja S. C. Mullick Road, Kolkata, West Bengal 700032, India

Received 3 November 2015; Revised 16 January 2016; Accepted 27 January 2016

Academic Editor: Miin-Shen Yang

Copyright © 2016 Pawan Kumar Singh 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.

  • Ritesh Sarkhel, Nibaran Das, Aritra Das, Mahantapas Kundu, and Mita Nasipuri, “A multi-scale deep quad tree based feature extraction method for the recognition of isolated handwritten characters of popular indic scripts,” Pattern Recognition, vol. 71, pp. 78–93, 2017. View at Publisher · View at Google Scholar
  • Jesús Monge-Álvarez, Carlos Hoyos-Barceló, Keshav Dahal, and Pablo Casaseca-de-la-Higuera, “Audio-cough event detection based on moment theory,” Applied Acoustics, vol. 135, pp. 124–135, 2018. View at Publisher · View at Google Scholar
  • Rahul Pramanik, Prabhat Dansena, and Soumen Bag, “A Study on the Effect of CNN-Based Transfer Learning on Handwritten Indic and Mixed Numeral Recognition,” Document Analysis and Recognition, vol. 1020, pp. 41–51, 2019. View at Publisher · View at Google Scholar