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Camilo et al., 2017 - Google Patents

A large comparison of feature-based approaches for buried target classification in forward-looking ground-penetrating radar

Camilo et al., 2017

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Document ID
7251241753839050406
Author
Camilo J
Collins L
Malof J
Publication year
Publication venue
IEEE Transactions on Geoscience and Remote Sensing

External Links

Snippet

Forward-looking ground-penetrating radar (FLGPR) has recently been investigated as a remote-sensing modality for buried target detection (eg, landmines). In this context, raw FLGPR data are beamformed into images, and then, computerized algorithms are applied to …
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Classifications

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