CNN-based 3D thermal modeling of the soil for antipersonnel mine detection

The inherent analogies between the defining equation of CNN and that of heat transfer are well known. In this paper, we explore the projection of a 3D thermal model of the soil on this kind of structure. In so doing, reliable and fast prediction of the thermodynamic behavior of soil subject to known...

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Bibliographic Details
Published inCellular Neural Networks and Their Applications: Nonlinear Information Processing and Intelligent Sensors pp. 307 - 314
Main Authors Lopez, P., Vilarino, D.L., Cabello, D.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2002
Subjects
Boundary conditions
Cellular neural networks
Equations
Heat transfer
Infrared detectors
Landmine detection
Nonhomogeneous media
Soil measurements
Thermal conductivity
Time measurement
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ISBN9789812381217
981238121X
DOI10.1109/CNNA.2002.1035065

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Summary:The inherent analogies between the defining equation of CNN and that of heat transfer are well known. In this paper, we explore the projection of a 3D thermal model of the soil on this kind of structure. In so doing, reliable and fast prediction of the thermodynamic behavior of soil subject to known boundary conditions can be obtained. That way, it is possible to characterize different kinds of soil in terms of its thermal signature. Based on that knowledge, and using an inverse approach, we perform the detection of buried land mines.
ISBN:9789812381217
981238121X
DOI:10.1109/CNNA.2002.1035065