Name
Title | ||
|---|---|---|
Supervised Farm Classification From Remote Sensing Images Based On Kernel Adatron Algorithm |
Abstract | ||
|---|---|---|
The main focus of this paper is to propose a new supervised farm classification method from remotely sensed Landsat7 ETM images and based on the kernel-adatron (KA) algorithm. This algorithm produces the separation of two farm classes by an optimal decision boundary defined by a linear separating hyperplane in a general feature space. Nonlinearities are handled by mapping the input data into a multidimensional feature space induced by a kernel function. The experimental results suggest that effective farm classification based on spectral characteristic recorded in a satellite image is possible; and reveals that repeatable relations between biophysical and spectral features can be derived from abstractions difficult to observe as farms. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/IGARSS.2007.4423561 | IGARSS: 2007 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-12: SENSING AND UNDERSTANDING OUR PLANET |
Keywords | Field | DocType |
multidimensional systems,feature space,image classification,kernel function,remote sensing,vectors,machine learning,kernel,clustering algorithms,satellites,artificial neural networks | Optimal decision,Computer science,Remote sensing,Artificial intelligence,Hyperplane,Contextual image classification,Kernel (linear algebra),Computer vision,Feature vector,Pattern recognition,Algorithm,Satellite image,Kernel (statistics) | Conference |
ISSN | Citations | PageRank |
2153-6996 | 0 | 0.34 |
References | Authors | |
4 | 8 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Adrian Gonzalez | 1 | 0 | 0.34 |
| Graham Russel | 2 | 0 | 0.34 |
| Astrid Márquez | 3 | 0 | 0.34 |
| José Alí Moreno | 4 | 65 | 8.60 |
| Cristina García | 5 | 19 | 3.56 |
| Carlos Domínguez | 6 | 0 | 0.34 |
| Omar Colmenares | 7 | 0 | 0.34 |
| Juan José Machado | 8 | 0 | 0.34 |