Name
Abstract | ||
|---|---|---|
In this paper, we present the visualization of image databases based on their primitive features. Our approach is to have a visual navigation tool for allowing the exploration and exploitation of large image archives. The tool is able to project the content of a given image database based on the primitive feature space and to provide interaction between the final user and the huge amount of data. Land Use/Land Cover area frame statistical Survey in-situ data are used as test dataset. Bag-of-Words and Weber Local Descriptors are used as primitive features. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/IGARSS.2016.7730543 | 2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) |
Keywords | Field | DocType |
Visual data mining, visualization, dimensionality reduction, land cover, land use | Data mining,Computer science,Image retrieval,Artificial intelligence,Land cover,Computer vision,Data visualization,Feature vector,Information retrieval,Information visualization,Visualization,Feature extraction,Visual Word | Conference |
ISSN | Citations | PageRank |
2153-6996 | 0 | 0.34 |
References | Authors | |
9 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daniela Espinoza-Molina | 1 | 54 | 8.83 |
| Kevin Alonso | 2 | 12 | 3.41 |
| Mihai Datcu | 3 | 893 | 111.62 |