Journal
IEEE TRANSACTIONS ON NEURAL NETWORKS
Volume 16, Issue 3, Pages 743-753Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNN.2005.844906
Keywords
hybrid artificial neural networks; landmine classification; landmine detection; scattering parameters
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Neural networks have been applied to landmine detection from data generated by different kinds of sensors. Real-valued neural networks have been used for detecting landmines from scattering parameters measured by ground penetrating radar (GPR) after disregarding phase information. This paper presents results using complex-valued neural networks, capable of phase-sensitive detection followed by classification. A two-layer hybrid neural network structure incorporating both supervised and unsupervised learning is proposed to detect and then classify the,types of landmines. Tests are also reported on a benchmark data.
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