DocumentCode
1576147
Title
Experts Fusion and Multilayer Perceptron Based on Belief Learning for Sonar Image Classification
Author
Martin, Arnaud ; Osswald, Christophe
Author_Institution
ENSIETA, Brest
fYear
2008
Firstpage
1
Lastpage
6
Abstract
The sonar images provide a rapid view of the seabed in order to characterize it. However, in such as uncertain environment, real seabed is unknown and the only information we can obtain, is the interpretation of different human experts, sometimes in conflict. In this paper, we propose to manage this conflict in order to provide a robust reality for the learning step of classification algorithms. The classification is conducted by a multilayer perceptron, taking into account the uncertainty of the reality in the learning stage. The results of this seabed characterization are presented on real sonar images.
Keywords
belief networks; image classification; learning (artificial intelligence); multilayer perceptrons; sonar imaging; belief learning; multilayer perceptron; sonar image classification; Classification algorithms; Humans; Image classification; Multilayer perceptrons; Pixel; Possibility theory; Sediments; Sonar navigation; Tiles; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Information and Communication Technologies: From Theory to Applications, 2008. ICTTA 2008. 3rd International Conference on
Conference_Location
Damascus
Print_ISBN
978-1-4244-1751-3
Electronic_ISBN
978-1-4244-1752-0
Type
conf
DOI
10.1109/ICTTA.2008.4530035
Filename
4530035
Link To Document