Pereira, D. R. [UNESP]Papa, J. P. [UNESP]Papa, L. P.Pisani, R. J.IEEE2019-10-032019-10-032018-01-01Igarss 2018 - 2018 Ieee International Geoscience And Remote Sensing Symposium. New York: Ieee, p. 7316-7319, 2018.2153-6996http://hdl.handle.net/11449/184129Satellite 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.7316-7319engLand-use classificationFinite Element MachinesRemote SensingTrabalho apresentado em eventoWOS:000451039807004Acesso aberto