Application of Numenta® Hierarchical Temporal Memory for land-use classification - A.J. Perea; J.E. Meroño; M.J. Aguilera (South African Journal of Science)
The aim of this paper is to present the application of memoryprediction theory, implemented in the form of a Hierarchical Temporal Memory (HTM), for land-use classification. Numenta®HTM is a new computing technology that replicates the structure and function of the human neocortex. In this study, a photogram, received by a photogrammetric UltraCamD® sensor of Vexcel, and data on 1 513 plots in Manzanilla (Huelva, Spain) were used to validate the classification, achieving an overall classification accuracy of 90.4%. The HTMapproach appears to hold promise for land-use classification.