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Institutional Repository [SANDBOX]
Technical University of Crete
Technical University of Crete
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| URI | http://purl.tuc.gr/dl/dias/7EAEF4C3-21FF-42F7-A0E0-1757D0FFAFE3 | - |
| Identifier | https://doi.org/10.3390/app11167531 | - |
| Identifier | https://www.mdpi.com/2076-3417/11/16/7531/htm | - |
| Language | en | - |
| Extent | 12 pages | en |
| Title | GPR data interpretation approaches in archaeological prospection | en |
| Creator | Manataki Meropi | en |
| Creator | Μανατακη Μεροπη | el |
| Creator | Vafeidis Antonios | en |
| Creator | Βαφειδης Αντωνιος | el |
| Creator | Sarris, Apostolos | en |
| Publisher | MDPI | en |
| Content Summary | This article focuses on the possible drawbacks and pitfalls in the GPR data interpretation process commonly followed by most GPR practitioners in archaeological prospection. Standard processing techniques aim to remove some noise, enhance reflections of the subsurface. Next, one has to calculate the instantaneous envelope and produce C-scans which are 2D amplitude maps showing high reflectivity surfaces. These amplitude maps are mainly used for data interpretation and provide a good insight into the subsurface but cannot fully describe it. The main limitations are discussed while studies aiming to overcome them are reviewed. These studies involve integrated interpretation approaches using both B-scans and C-scans, attribute analysis, fusion approaches, and recent attempts to automatically interpret C-scans using Deep Learning (DL) algorithms. To contribute to the automatic interpretation of GPR data using DL, an application of Convolutional Neural Networks (CNNs) to classify GPR data is also presented and discussed. | en |
| Type of Item | Ανασκόπηση | el |
| Type of Item | Review | en |
| License | http://creativecommons.org/licenses/by/4.0/ | en |
| Date of Item | 2022-10-11 | - |
| Date of Publication | 2021 | - |
| Subject | Ground Penetrating Radar | en |
| Subject | Archaeological prospection | en |
| Subject | Data interpretation | en |
| Subject | Convolutional Neural Networks | en |
| Subject | AlexNet | en |
| Bibliographic Citation | M. Manataki, A. Vafidis, and A. Sarris, “GPR data interpretation approaches in archaeological prospection,” Appl. Sci., vol. 11, no. 16, Aug. 2021, doi: 10.3390/app11167531. | en |
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