Resumen

PEREA, A.J.; MERONO, J.E.  y  AGUILERA, M.J.. Application of Numenta^® Hierarchical Temporal Memory for land-use classification. S. Afr. j. sci. [online]. 2009, vol.105, n.9-10, pp.370-375. ISSN 1996-7489.

The aim of this paper is to present the application of memory-prediction 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 HTM approach appears to hold promise for land-use classification.

Palabras clave : memory-prediction theory; NuPIC^®; UltraCamD^® sensor; Hierarchical Temporal Memory.

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