Table of Contents Author Guidelines Submit a Manuscript
Mathematical Problems in Engineering
Volume 2018, Article ID 3598316, 7 pages
https://doi.org/10.1155/2018/3598316
Research Article

Object Detection Based on Fast/Faster RCNN Employing Fully Convolutional Architectures

1ATR National Lab, National University of Defense Technology, Changsha 410073, China
2State Key Lab of Complex Electromagnetic Environment Effects on Electronics and Information System, National University of Defense Technology, Changsha 410073, China

Correspondence should be addressed to Yun Ren; moc.361@tdun_nuyner

Received 23 October 2017; Accepted 12 December 2017; Published 9 January 2018

Academic Editor: Francesco Marotti de Sciarra

Copyright © 2018 Yun Ren 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 [2 citations]

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

  • Yun Ren, Changren Zhu, and Shunping Xiao, “Deformable Faster R-CNN with Aggregating Multi-Layer Features for Partially Occluded Object Detection in Optical Remote Sensing Images,” Remote Sensing, vol. 10, no. 9, pp. 1470, 2018. View at Publisher · View at Google Scholar
  • Yun Ren, Changren Zhu, and Shunping Xiao, “Small Object Detection in Optical Remote Sensing Images via Modified Faster R-CNN,” Applied Sciences, vol. 8, no. 5, pp. 813, 2018. View at Publisher · View at Google Scholar