| Título |
Geospatial Raster Data Processing Applying Neural Networks |
| Tipo |
Congreso |
| Sub-tipo |
Memoria |
| Descripción |
13th International Conference on Telematics and Computing, WITCOM 2024 |
| Resumen |
This work proposes applying machine learning techniques to classify raster geospatial data, which have traditionally been classified using classic segmentation and clustering techniques. In the first instance, we propose a neural network model using a multilayer perceptron model to carry out the classification task. Such a model can be trained directly by the data samples due to the nature of the raster geospatial data, which has several bands that serve as a spectral signature and will be used for expressed training tasks. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. |
| Observaciones |
DOI 10.1007/978-3-031-77293-1_11
Communications in Computer and Information Science, v. 2250 |
| Lugar |
Mazatlán |
| País |
Mexico |
| No. de páginas |
141-153 |
| Vol. / Cap. |
v. 2250 CCIS |
| Inicio |
2024-11-04 |
| Fin |
2024-11-08 |
| ISBN/ISSN |
9783031772924 |
