@inproceedings{0ae56dd037ce4f369fda98436e6c7469,
title = "How transferable are downward-looking and handheld ground penetrating radar data? Experiments in the context of buried threat detection",
abstract = "In this work we consider the problem of developing algorithms for the automatic detection of buried threats using handheld Ground Penetrating Radar (HH-GPR) data. The development of algorithms for HH-GPR is relatively nascent compared to algorithm development efforts for larger downward-looking GPR (DL-GPR) systems. One of the biggest bottlenecks for the development of algorithms is the relative scarcity of labeled HH-GPR data that can be used for development. Given the similarities between DL-GPR data and HH-GPR data however, we hypothesized that it may be possible to utilize DL-GPR data to support the development of algorithms for HH-GPR. In this work we assess the detection performance of a HH-GPR-based BTD algorithm as we vary the amounts and characteristics of the DL-GPR data included in the development of HH-GPR detection algorithms. The results indicate that supplementing HH-GPR data with DL-GPR does improve performance, especially when including data collected over buried threat locations.",
keywords = "Transfer learning, algorithm, buried threat detection, feature extraction, ground penetrating radar, handheld",
author = "Evan Stump and Daniel Reichman and Collins, {Leslie M.} and Malof, {Jordan M.}",
note = "Publisher Copyright: Copyright {\textcopyright} 2019 SPIE.; Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIV 2019 ; Conference date: 15-04-2019 Through 17-04-2019",
year = "2019",
doi = "10.1117/12.2519969",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Bishop, {Steven S.} and Isaacs, {Jason C.}",
booktitle = "Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIV",
}