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We integrate several key components of a pattern recognition system for a mine-like targets detection problem. These include several image enhancements, postprocessing and multi-expert fusion. The image enhancement includes wavelet de-noising and classical computer vision methods such as nonlinear and adaptive equalization and other filters. Our approach(More)
| Underwater mammal sound classiication is demonstrated using a novel application of wavelet time/frequency decomposition and feature extraction using a BCM unsupervised network. Diierent feature extraction methods and diierent wavelet representations are studied. The system achieves outstanding classiication performance even when tested with mammal sounds(More)
Underwater mammal sound classification is demonstrated using a novel application of wavelet time–frequency decomposition and feature extraction using a Bienenstock, Cooper, and Munro (BCM) unsupervised network. Different feature extraction methods and different wavelet representations are studied. The system achieves outstanding classification performance(More)
| Underwater mammal sound classiication is demonstrated using a novel application of wavelet time/frequency decomposition and feature extraction using a BCM unsupervised network. Diierent feature extraction methods and diierent wavelet representations are studied. The system achieves outstanding classiication performance even when tested with mammal sounds(More)
Good discrimination results have been obtained with an active backscatter data set of minelike objects [1], where the task was to distinguish between man-made and non-man-made objects. In this work we introduce a novel method for constructing best basis for discrimination from wavelet packets, and demonstrate the superiority of multiple ensembles of(More)
A common problem in genomics is to test for associations between two or more genomic features, typically represented as intervals interspersed across the genome. Existing methodologies can test for significant pairwise associations between two genomic intervals; however, they cannot test for associations involving multiple sets of intervals. This limits our(More)
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