DocumentCode :
2286505
Title :
CNN-based 3D thermal modeling of the soil for antipersonnel mine detection
Author :
Lopez, Pierre ; Vilarino, D.L. ; Cabello, D.
Author_Institution :
Dept. of Electron. & Comput. Sci., Santiago de Compostela Univ.
fYear :
2002
fDate :
22-24 Jul 2002
Firstpage :
307
Lastpage :
314
Abstract :
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.
Keywords :
cellular neural nets; heat transfer; infrared imaging; inverse problems; landmine detection; partial differential equations; soil; terrestrial heat; antipersonnel mine detection; boundary conditions; buried land mine detection; cellular neural net based 3D thermal modeling; heat transfer; inverse approach; soil; thermal signature; thermodynamic behavior; Boundary conditions; Cellular neural networks; Equations; Heat transfer; Infrared detectors; Landmine detection; Nonhomogeneous media; Soil measurements; Thermal conductivity; Time measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cellular Neural Networks and Their Applications, 2002. (CNNA 2002). Proceedings of the 2002 7th IEEE International Workshop on
Print_ISBN :
981-238-121-X
Type :
conf
DOI :
10.1109/CNNA.2002.1035065
Filename :
1035065
Link To Document :
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