Literature DB >> 15555861

Plastic mine detecting radar system using complex-valued self-organizing map that deals with multiple-frequency interferometric images.

Takahiro Hara1, Akira Hirose.   

Abstract

Ground penetrating radars (GPR's) have been often applied to underground object imaging. However, conventional radar systems do not work sufficiently to detect anti-personnel plastic landmines. We propose a novel radar imaging system, which processes adaptively interferometric front-end data obtained at multiple-frequency points. The system deals with interferometric images using complex-valued self-organizing map (C-SOM). We demonstrate a successful visualization of a plastic mine buried near the ground surface.

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Year:  2004        PMID: 15555861     DOI: 10.1016/j.neunet.2004.07.012

Source DB:  PubMed          Journal:  Neural Netw        ISSN: 0893-6080


  1 in total

1.  Fast Recall for Complex-Valued Hopfield Neural Networks with Projection Rules.

Authors:  Masaki Kobayashi
Journal:  Comput Intell Neurosci       Date:  2017-05-03
  1 in total

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