Actas de congresos
Land-use classification using Finite Element Machines
Fecha
2018-10-31Registro en:
International Geoscience and Remote Sensing Symposium (IGARSS), v. 2018-July, p. 7316-7319.
10.1109/IGARSS.2018.8519252
2-s2.0-85064177102
Autor
Universidade Estadual Paulista (Unesp)
Faculty Southwest Paulista
University of Alfenas
Institución
Resumen
Satellite images have been used in a number of applications, both in the academy and in the industry. One critical purpose concerns the land-use classification, which aims at automatically identifying different land-use applications, which range from economy and environmental monitoring to resources planning. In this paper, we introduce a new machine learning technique called Finite Element Machines (FEMa) in the context of land-use classification using satellite images. We show that FEMa can obtain results that are comparable to some state-of-the-art techniques in the literature.