Name
Title | ||
|---|---|---|
Dimensionality reduction of hyperspectral data: Assessing the performance of Autoassociative Neural Networks |
Abstract | ||
|---|---|---|
Feature extraction for the dimensionality reduction of hyperspectral data is performed by means of Auto-Associative Neural Networks. The algorithm performance is compared to the Principal Component Analysis and the Maximum Noise Fraction ones. Results of land cover pixel-based maps yielded by the reduced vector and a dedicated neural network classification algorithm are also reported. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/IGARSS.2010.5652586 | Geoscience and Remote Sensing Symposium |
Keywords | Field | DocType |
feature extraction,geophysical image processing,neural nets,principal component analysis,terrain mapping,autoassociative neural network,dimensionality reduction,feature extraction,hyperspectral data,land cover pixel-based map,maximum noise fraction,neural network classification,principal component analysis,reduced vector,Hyperspectral data,autoassociative neural networks,dimensionality reduction,land cover | Neural network classification,Computer vision,Dimensionality reduction,Pattern recognition,Computer science,Hyperspectral imaging,Feature extraction,Artificial intelligence,Pixel,Artificial neural network,Land cover,Principal component analysis | Conference |
ISSN | ISBN | Citations |
2153-6996 E-ISBN : 978-1-4244-9564-1 | 978-1-4244-9564-1 | 3 |
PageRank | References | Authors |
0.41 | 4 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Giorgio Licciardi | 1 | 471 | 25.71 |
| Fabio Del Frate | 2 | 508 | 72.43 |
| Giovanni Schiavon | 3 | 123 | 24.55 |
| Domenico Solimini | 4 | 65 | 15.10 |