| Revista: | Boletim de ciencias geodesicas |
| Base de datos: | PERIÓDICA |
| Número de sistema: | 000458660 |
| ISSN: | 1413-4853 |
| Autores: | Casaroti, Carla Jaqueline1 Centeno, Jorge Antonio Silva1 Fuchs, Stephan2 |
| Instituciones: | 1Universidade Federal do Parana, Departamento de Geomatica, Curitiba, Parana. Brasil 2Karlsruher Institut für Technologie, Fachbereich Siedlungswasserwirtschaft und Wassergütewirtschaft, Karlsruhe. Alemania |
| Año: | 2020 |
| Volumen: | 26 |
| Número: | 3 |
| País: | Brasil |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Enfoque: | Analítico, descriptivo |
| Resumen en inglés | The use of OBIA for high spatial resolution image classification can be divided in two main steps, the first being segmentation and the second regarding the labeling of the objects in accordance with a particular set of features and a classifier. Decision trees are often used to represent human knowledge in the latter. The issue falls in how to select a smaller amount of features from a feature space with spatial, spectral and textural variables to describe the classes of interest, which engenders the matter of choosing the best or more convenient feature selection (FS) method. In this work, an approach for FS within a decision tree was introduced using a single perceptron and the Backpropagation algorithm. Three alternatives were compared: single, double and multiple inputs, using a sequential backward search (SBS). Test regions were used to evaluate the efficiency of the proposed methods. Results showed that it is possible to use a single perceptron in each node, with an overall accuracy (OA) between 77.6% and 77.9%. Only SBS reached an OA larger than 88%. Thus, the quality of the proposed solution depends on the number of input features |
| Disciplinas: | Geociencias |
| Palabras clave: | Cartografía, Imagen de alta resolución espacial, Selección de características, Perceptron, Arbol de decisiones |
| Keyword: | Cartography, High spatial resolution image, Feature selection, Perceptron, Decision tree |
| Texto completo: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
