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Journal of Electrical and Computer Engineering
Volume 2013, Article ID 908906, 2 pages

Algorithms for Multispectral and Hyperspectral Image Analysis

1Sensors and Electron Devices Directorate, US Army Research Laboratory, Adelphi, MD 20783, USA
2Department of Mathematics, Wake Forest University, Winston-Salem, NC 27106, USA
3Space Data Systems Group, Los Alamos National Laboratory, Los Alamos, NM 87545, USA
4Department of Electrical and Computer Engineering, University of Missouri, Columbia, MO 65211, USA

Received 28 November 2012; Accepted 28 November 2012

Copyright © 2013 Heesung Kwon 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.

  • Sarath R. Nair, Nidhin Prabhakar, Sachin Kumar, and Midhun, “Deep model for classification of hyperspectral image using restricted Boltzmann machine,” ACM International Conference Proceeding Series, vol. 10-11-, 2014. View at Publisher · View at Google Scholar
  • T.V. Nidhin Prabhakar, Gintu Xavier, P. Geetha, and K.P. Soman, “Spatial Preprocessing Based Multinomial Logistic Regression for Hyperspectral Image Classification,” Procedia Computer Science, vol. 46, pp. 1817–1826, 2015. View at Publisher · View at Google Scholar
  • Bo Du, Lefei Zhang, Rui Zhao, and Liangpei Zhang, “A spectral-spatial based local summation anomaly detection method for hyperspectral images,” Signal Processing, vol. 124, pp. 115–131, 2016. View at Publisher · View at Google Scholar