Deep Convolutional Neural Networks With Integrated Quadratic Correlation Filters For Automatic Target Recognition

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.

Publication Date

12-13-2018

Publication Title

IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

Volume

2018-June

Number of Pages

1303-1310

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/CVPRW.2018.00168

Socpus ID

85060852157 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85060852157

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