Deep Convolutional Neural Networks with Integrated Quadratic Correlation Filters for Automatic Target Recognition

Brian Millikan, Hassan Foroosh, Qiyu Sun

CVPRW 2018 pp. 1222-1229

doi:10.1109/CVPRW.2018.00168 /cvprw/2018/millikan2018cvprw-deep/

Abstract

Automatic target recognition involves detecting and recognizing potential targets automatically, which is widely used in civilian and military applications today. Quadratic correlation filters were introduced as two-class recognition classifiers for quickly detecting targets in cluttered scene environments. In this paper, we introduce two methods that integrate the discrimination capability of quadratic correlation filters with the multi-class recognition ability of multilayer neural networks. For mid-wave infrared imagery, the proposed methods are demonstrated to be multi-class target recognition classifiers with very high accuracy.

CVPRW Semantic Scholar

Cite

Text

Millikan et al. "Deep Convolutional Neural Networks with Integrated Quadratic Correlation Filters for Automatic Target Recognition." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2018. doi:10.1109/CVPRW.2018.00168

Markdown

[Millikan et al. "Deep Convolutional Neural Networks with Integrated Quadratic Correlation Filters for Automatic Target Recognition." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2018.](https://mlanthology.org/cvprw/2018/millikan2018cvprw-deep/) doi:10.1109/CVPRW.2018.00168

BibTeX

@inproceedings{millikan2018cvprw-deep,
  title     = {{Deep Convolutional Neural Networks with Integrated Quadratic Correlation Filters for Automatic Target Recognition}},
  author    = {Millikan, Brian and Foroosh, Hassan and Sun, Qiyu},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2018},
  pages     = {1222-1229},
  doi       = {10.1109/CVPRW.2018.00168},
  url       = {https://mlanthology.org/cvprw/2018/millikan2018cvprw-deep/}
}