Name
Title | ||
|---|---|---|
Quantitative Evaluation of the Feature Space Transformation Methods Used for Applications of Visual Semantic Clustering of EO Images. |
Abstract | ||
|---|---|---|
Data visualization guides the process of indexing and retrieval, strengthening the link between low-level image features and high-level human understanding of image content. In this regard, we have described the semantic content of a multidimensional dataset using its descriptors to derive high-dimensional feature spaces. The dimensionality of these spaces is further reduced to three in order to p... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/JSTARS.2017.2681202 | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Keywords | Field | DocType |
Remote sensing,Semantics,Principal component analysis,Visualization,Data visualization,Earth,Redundancy | Data mining,Dimensionality reduction,Feature selection,Computer science,Remote sensing,Search engine indexing,Artificial intelligence,Computer vision,Feature vector,Data visualization,Feature (computer vision),Visualization,Curse of dimensionality | Journal |
Volume | Issue | ISSN |
10 | 6 | 1939-1404 |
Citations | PageRank | References |
0 | 0.34 | 17 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andreea Griparis | 1 | 5 | 1.45 |
| Daniela Faur | 2 | 20 | 4.71 |
| Mihai Datcu | 3 | 893 | 111.62 |