Name
Abstract | ||
|---|---|---|
In the ground-penetrating radar (GPR) B-scan images, various noise sources are superimposed due to the ruggedness of the surface, sensor vibration, and multiple reflections. Additionally, the intensity of the received signals from small-size or low-metal-content landmines is low. Thus, it is difficult to accurately detect buried mines. In this letter, we propose an effective method to improve the ... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/LGRS.2018.2809720 | IEEE Geoscience and Remote Sensing Letters |
Keywords | Field | DocType |
Histograms,Landmine detection,Ground penetrating radar,Image enhancement,Computational modeling,Shape,Permittivity | Radar,Computer vision,Histogram,Permittivity,Ground-penetrating radar,Effective method,Ultra-wideband,Artificial intelligence,Vibration,Ac components,Mathematics | Journal |
Volume | Issue | ISSN |
15 | 5 | 1545-598X |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Minju Kim | 1 | 0 | 3.04 |
| Seong-Dae Kim | 2 | 184 | 25.81 |
| Jonghun Hahm | 3 | 0 | 0.68 |
| Dong-Hyun Kim | 4 | 35 | 5.54 |
| Soonho Hong | 5 | 0 | 0.34 |