Title | ||
---|---|---|
Deep Convolutional Neural Networks with Integrated Quadratic Correlation Filters for Automatic Target Recognition |
Abstract | ||
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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. |
Year | DOI | Venue |
---|---|---|
2018 | 10.1109/CVPRW.2018.00168 | 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) |
Keywords | Field | DocType |
two-class recognition classifiers,multilayer neural networks,multiclass target recognition classifiers,convolutional neural networks,automatic target recognition,military applications,civilian applications,mid-wave infrared imagery,quadratic correlation filters,target detection,cluttered scene environment | Computer vision,Object detection,Pattern recognition,Automatic target recognition,Convolutional neural network,Computer science,Infrared imagery,Quadratic equation,Correlation,Artificial intelligence,Artificial neural network | Conference |
ISSN | ISBN | Citations |
2160-7508 | 978-1-5386-6101-7 | 0 |
PageRank | References | Authors |
0.34 | 9 | 3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Brian Millikan | 1 | 2 | 0.77 |
Hassan Foroosh | 2 | 251 | 14.66 |
Qiyu Sun | 3 | 2 | 1.39 |