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The Scientific World Journal
Volume 2014, Article ID 140930, 17 pages
Research Article

Analysis of Infrared Signature Variation and Robust Filter-Based Supersonic Target Detection

1Yeungnam University, Gyeongsan-si, Gyeongsangbuk-do 712-749, Republic of Korea
2Agency for Defense Development, 111 Sunam-dong, Daejeon 305-152, Republic of Korea
3Electromagnetic Technology Laboratory, POSTECH, Pohang 790-784, Republic of Korea

Received 22 August 2013; Accepted 17 November 2013; Published 11 February 2014

Academic Editors: S. Bourennane and J. Marot

Copyright © 2014 Sungho Kim 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 [4 citations]

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

  • Sungho Kim, Woo-Jin Song, and So-Hyun Kim, “Infrared Variation Optimized Deep Convolutional Neural Network for Robust Automatic Ground Target Recognition,” 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 195–202, . View at Publisher · View at Google Scholar
  • Ihsan Ullah, Taek Lyul Song, and Thia Kirubarajan, “Active vehicle protection using angle and time-to-go information from high-resolution infrared sensors,” Optical Engineering, vol. 54, no. 5, 2015. View at Publisher · View at Google Scholar
  • Xin Wu, and Jianqi Zhang, “Signature simulation of infrared target by tracing multiple areal sources,” Applied Optics, vol. 54, no. 13, pp. 3842–3848, 2015. View at Publisher · View at Google Scholar
  • Sungho Kim, “Infrared variation reduction by simultaneous background suppression and target contrast enhancement for deep convolutional neural network-based automatic target recognition,” Optical Engineering, vol. 56, no. 6, 2017. View at Publisher · View at Google Scholar