DocumentCode :
1968114
Title :
Minehunting with multi-layer perceptrons
Author :
Shazeer, Dov J. ; Bello, Martin G.
Author_Institution :
Charles Stark Draper Lab., Cambridge, MA, USA
fYear :
1991
fDate :
15-17 Aug 1991
Firstpage :
57
Lastpage :
68
Abstract :
The authors describe the use of multilayer perceptrons to solve the problem of distinguishing mine-like objects from clutter. Three increasingly sophisticated and effective approaches were applied against difficult side scan sonar imagery containing a highly cluttered and variable environment. Performances of the three approaches are compared using receiver operating curves (ROCs). Comparisons show that one can achieve a detection rate of 0.97 for a 0.01 false alarm rate. A subset of the networks have been demonstrated on special purpose hardware to run in real time
Keywords :
acoustic signal processing; clutter; neural nets; pattern recognition; picture processing; sonar; clutter; detection rate; false alarm rate; mine-like objects; multi-layer perceptrons; multilayer perceptrons; real time; receiver operating curves; side scan sonar imagery; Artificial neural networks; Frequency; Humans; Laboratories; Layout; Multilayer perceptrons; Neural networks; Pattern recognition; Sonar applications; Underwater vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks for Ocean Engineering, 1991., IEEE Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-0205-2
Type :
conf
DOI :
10.1109/ICNN.1991.163328
Filename :
163328
Link To Document :
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