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An Overview and Recent Advances in Fuzzy ARTMAP Classifier Usage for Mapping Purposes Using Remotely Sensed Data

P. F. Prado1*, I. C. S. Duarte2

  1. Department of Earth Physics and Thermodynamics, University of Valencia, Valencia, Valencian Community 50 46100, Spain
  2. Department of Biology, Federal University of São Carlos, Sorocaba, São Paulo 18052-780, Brazil

*Corresponding author. fax: +55 15 32297543. E-mail address: (P. F. Prado).


This paper presents an overview and recent advances on the usage of Fuzzy ARTMAP artificial neural network architecture (and its variants) for mapping purposes using remotely sensed data. It aims to offer a perspective into the past and ongoing developments of this specific research field. Moreover, this paper suggests initial pathways for those who intend to perform a scientific investigation using this artificial neural network architecture. Some applications of this architecture in other research fields are highlighted for general knowledge purposes, as well as suggestions of code repositories to implement it. Possible gaps in the literature related to Fuzzy ARTMAP classifier usage for mapping are suggested, leading to paths for future developments in this field of research.

Keywords: images, land cover, land use, mapping, machine learning, neuro-fuzzy, sensors

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