Land-use classification using Finite Element Machines
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Institute of Electrical and Electronics Engineers (IEEE)
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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.
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International Geoscience and Remote Sensing Symposium (IGARSS), v. 2018-July, p. 7316-7319.
