DocumentCode :
2144003
Title :
Research on decision fusion in underwater target recognition
Author :
Yong, Jun ; Zhu, Ruo-qian
Author_Institution :
Science and Technology on Underwater Acoustic Laboratory, Harbin Engineering University, China
fYear :
2010
fDate :
4-6 Dec. 2010
Firstpage :
2334
Lastpage :
2337
Abstract :
Aimed at enhancing the adaptive information fusion capability of underwater target recognition in complex environment, we employed the decision fusion technology based on the Dempster-Shafer Theory. The information fusion model presented in this paper utilized neural networks and fuzzy theory, which is the basic theory for this model, to analyze the uncertainty of probe and apply it to information fusion of underwater target recognition. By fusing several target features, the model was able to improve the recognition ratio for targets. Through the treatment of experimental data, this paper validated that the method does increase the accuracy and validity of underwater target recognition and the credibility had been greatly improved.
Keywords :
Classification algorithms; Feature extraction; Fuses; Pattern recognition; Support vector machine classification; Target recognition; Training; Feature extraction; information fusion; neural network; target recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science and Engineering (ICISE), 2010 2nd International Conference on
Conference_Location :
Hangzhou, China
Print_ISBN :
978-1-4244-7616-9
Type :
conf
DOI :
10.1109/ICISE.2010.5691035
Filename :
5691035
Link To Document :
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