Name
Abstract | ||
|---|---|---|
Recently, a promising pattern-recognition system has been presented to deal with the extraction of buried-object characteristics in ground-penetrating-radar images. In particular, it allows the detecting of buried objects by means of a search method based on genetic algorithms and the recognizing of the material type of the identified objects through a classification approach based on support vect... |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/LGRS.2009.2028697 | IEEE Geoscience and Remote Sensing Letters |
Keywords | Field | DocType |
Gaussian processes,Buried object detection,Ground penetrating radar,Feature extraction,Object detection,Pattern recognition,Shape,Genetic algorithms,Support vector machines,Support vector machine classification | Ground-penetrating radar,Remote sensing,Gaussian process,Artificial intelligence,Genetic algorithm,Computer vision,Object detection,Pattern recognition,Regression,Support vector machine,Feature extraction,Mathematics,Pattern recognition system | Journal |
Volume | Issue | ISSN |
7 | 1 | 1545-598X |
Citations | PageRank | References |
1 | 0.35 | 4 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Edoardo Pasolli | 1 | 285 | 17.04 |
| Farid Melgani | 2 | 1100 | 80.98 |
| Massimo Donelli | 3 | 76 | 6.83 |