Nonparametric Bayesian Context Learning for Buried Threat Detection

Nonparametric Bayesian Context Learning for Buried Threat Detection

<p>This dissertation addresses the problem of detecting buried explosive threats (i.e., landmines and improvised explosive devices) with ground-penetrating radar (GPR) and hyperspectral imaging (HSI) across widely-varying environmental conditions. Automated detection of buried objects with GPR...

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Bibliographic Details
Main Author: Ratto, Christopher Ralph
Other Authors: Collins, Leslie M.
Published: 2012
Subjects:
Electrical engineering
Statistics
Bayesian inference
Ground-penetrating radar
Hyperspectral
Landmine detection
Machine learning
Signal processing
Online Access:http://hdl.handle.net/10161/5413

Internet

http://hdl.handle.net/10161/5413

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