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