Land-use classification using Finite Element Machines - Pereira, D. R. [UNESP]; Papa, J. P. [UNESP]; Papa, L. P.; Pisani, R. J. (Institute of Electrical and Electronics Engineers (IEEE), 2018)
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.
Keywords: Finite element machines; Land-use classification; Remote sensing