Material Classification of Underground Objects from GPR Recordings Using Deep Learning Approach

Author:

Štifanić Daniel,Štifanić Jelena,Šegota Sandi Baressi,Anđelić Nikola,Car Zlatan

Publisher

Springer Nature Switzerland

Reference18 articles.

1. Krause, A., Perciavalle, P., Johnson, K., Owens, B., Frodl, D., Sarni, W., Foundry, W.: The digitization of water

2. Jol, H.M. (ed.) Ground penetrating radar theory and applications. Elsevier, 8 December 2008

3. Lu, Q., Pu, J., Liu, Z.: Feature extraction and automatic material classification of underground objects from ground penetrating radar data. J. Electr. Comput. Eng. 2014, 28 (2014)

4. Besaw, L.E., Stimac, P.J.: Deep convolutional neural networks for classifying GPR B-scans. In Detection and sensing of mines, explosive objects, and obscured targets XX 2015 May 21, vol. 9454, pp. 385–394). SPIE (2015)

5. Baker, G.S., Jordan, T.E., Pardy, J.: An introduction to ground penetrating radar (GPR)

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