Demining sensor modeling and feature-level fusion by Bayesian networks

  title={Demining sensor modeling and feature-level fusion by Bayesian networks},
  author={Silvia Ferrari and Adriano Vaghi},
  journal={IEEE Sensors Journal},
A method for obtaining the Bayesian network (BN) representation of a sensor's measurement process is developed so that the problems of sensor fusion and management can be approached from a unified point of view. Uncertainty, reliability, and causal information embedded in the sensor data are used to build the BN model of a sensor. The method is applied to model ground-penetrating radar, electromagnetic induction, and infrared sensors for humanitarian demining. Structural and parameter learning… CONTINUE READING
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Publications referenced by this paper.
Showing 1-10 of 26 references

Sensor Management by a Graphical Model Approach,

  • A. Vaghi
  • Laurea thesis, Dept. Elect. Eng.,
  • 2004
Highly Influential
5 Excerpts

and G

  • K. C. Baumbgartner, S. Ferrari
  • C. Salfati, “Bayesian network modeling of…
  • 2005
2 Excerpts

Extraction of ground penetrating radar for mine detection,

  • S. Chang, M. F. Ruane
  • Proc. SPIE, vol. 5089,
  • 2003

and H

  • T. G. Savelyev, L. Van Kempen
  • Sahli, “GPR anti-personnel mine detection…
  • 2003

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