DocumentCode :
536252
Title :
The identification research of airplane target based on BP neural network
Author :
Yang, Guang ; Zhang, Bai ; Wang, Xiaojuan ; Zhang, Jianfeng ; Pang, Zhenyu ; Li, Hang ; Yang, Xianghua
Author_Institution :
Special Profession Dept., Aviation Univ. of Air Force, Changchun, China
Volume :
1
fYear :
2010
fDate :
29-31 Oct. 2010
Firstpage :
727
Lastpage :
729
Abstract :
The airplane goal´s automatic identification is a research hot spot which realizing the target automatic recognition of the remote sensing image. The BP neural network is a multi-layered network which using the non-linear differentiable function to carry on the weight training. It has contained the most essence part in the neural network theory; the BP neural network has obtained the widespread application in the domains of function approach, pattern Identification, information class and data compression because of its simple structure. Identified and researched the type of airplane based on the artificial neural networks method using the MATLAB software. The result indicated: the accuracy of airplane target recognition may achieve 72.1% based on the BP neural network and it can meet the needs.
Keywords :
aircraft; backpropagation; data compression; geophysical image processing; image classification; neural nets; object detection; object recognition; remote sensing; BP neural network; MATLAB; airplane goal automatic identification; artificial neural network; data compression; multilayered network; nonlinear differentiable function; pattern Identification; remote sensing image; target recognition; Adaptation model; Atmospheric modeling; Biological system modeling; Computer languages; Image recognition; Mathematical model; Target recognition; Airplane target; BP Neural Network; Network training; Pattern Identification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4244-6582-8
Type :
conf
DOI :
10.1109/ICICISYS.2010.5658501
Filename :
5658501
Link To Document :
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