In this paper, an aircraft recognition system using a neural network is presented. A 2-D perspective view of aircraft models is first normalized through the preprocessing stage using bilinear interpolation and principal component analysis. The new patterns are invariant to translation, dilation, and rotation. Then, the Kohonen and Grossberg neural networks were trained using a small number of normalized patterns. The presented algorithm was tested on partially incomplete, noisy and geometrically distorted images and it was found that the recognition performance is 100% with six referenced aircraft.
Somaie, A., Badr, A., & Salah, T. (1999). FROM NEURAL NETWORK TO AIRCRAFT RECOGNITION SYSTEM. The International Conference on Electrical Engineering, 2(2nd International Conference on Electrical Engineering ICEENG 1999), 305-311. doi: 10.21608/iceeng.1999.62514
MLA
A. A. Somaie; A. Badr; T. Salah. "FROM NEURAL NETWORK TO AIRCRAFT RECOGNITION SYSTEM", The International Conference on Electrical Engineering, 2, 2nd International Conference on Electrical Engineering ICEENG 1999, 1999, 305-311. doi: 10.21608/iceeng.1999.62514
HARVARD
Somaie, A., Badr, A., Salah, T. (1999). 'FROM NEURAL NETWORK TO AIRCRAFT RECOGNITION SYSTEM', The International Conference on Electrical Engineering, 2(2nd International Conference on Electrical Engineering ICEENG 1999), pp. 305-311. doi: 10.21608/iceeng.1999.62514
VANCOUVER
Somaie, A., Badr, A., Salah, T. FROM NEURAL NETWORK TO AIRCRAFT RECOGNITION SYSTEM. The International Conference on Electrical Engineering, 1999; 2(2nd International Conference on Electrical Engineering ICEENG 1999): 305-311. doi: 10.21608/iceeng.1999.62514
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