Name
Title | ||
|---|---|---|
Cueing, feature discovery, and one-class learning for synthetic aperture radar automatic target recognition |
Abstract | ||
|---|---|---|
The exquisite capabilities of biological neural systems for recognizing target patterns subject to large variations have motivated us to investigate neurophysiologically-inspired techniques for automatic target recognition. This paper describes a modular multi-stage architecture for focus-of-attention cueing, feature discovery and extraction, and one-class pattern learning and identification in synthetic aperture radar imagery. To prescreen massive amounts of image data, we apply a focus-of-attention algorithm using data skewness to extract man-made objects from natural clutter regions. We apply self-organizing feature discovery algorithms that uniquely characterize targets in a reduced dimension space and use self-organizing one-class classifiers for learning target variations. We also develop a distance metric for partial obscuration recognition. We present performance results using simulated SAR data and test for within-class generalization using nontrained targets including both in-the-clear and partially obscured examples. We test for between-class generalization using non-trained targets including both in-the-clear and partially obscured examples. We test for between-class generalization using near-target data. |
Year | DOI | Venue |
|---|---|---|
1995 | 10.1016/0893-6080(95)00049-6 | Neural Networks |
Keywords | Field | DocType |
cueing using focus-of-attention,automatic target recognition,feature discovery using neocognitron and generalized hebbian algorithm,synthetic aperture radar,feature discovery,partial obscuration recognition using hyperstar metric,one-class classification using adaptive resonance theory (art 2-a),adaptive resonance theory,one class classification,distance metric,self organization | Computer vision,Skewness,Automatic target recognition,Synthetic aperture radar,Clutter,Metric (mathematics),Artificial intelligence,Modular design,Feature discovery,Artificial neural network,Mathematics,Machine learning | Journal |
Volume | Issue | ISSN |
8 | 7-8 | Neural Networks |
Citations | PageRank | References |
40 | 5.60 | 15 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mark W. Koch | 1 | 92 | 10.60 |
| Mary M. Moya | 2 | 101 | 16.90 |
| Larry D. Hostetler | 3 | 40 | 5.60 |
| R. Joseph Fogler | 4 | 40 | 5.60 |