Deep convolutional neural network target classification for underwater synthetic aperture sonar imagery-Reference-Cited by-同舟云学术

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Deep convolutional neural network target classification for underwater synthetic aperture sonar imagery

Published:2019-05-10 Issue: Volume: Page:
ISSN:
Container-title:Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIV
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Author:

Galusha Aquila P.,Dale Jeff,Keller James,Zare Alina

Publisher

SPIE

Reference13 articles.

1. A fast target detection algorithm for underwater synthetic aperture sonar imagery

2. Kernel RX-Algorithm: A Nonlinear Anomaly Detector for Hyperspectral Imager;Kwon;IEEE transactions on Geoscience and Remote Sensing,2005

3. Rapid object detection using a boosted cascade of simple features

4. A new approach for mine detection in SAS imagery

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