SciELO - Scientific Electronic Library Online

vol.105 número9-10Experimental response of an optical sensor used to determine the moment of blast by sensing the flash of the explosionFemtosecond pump probe spectroscopy for the study of energy transfer of light-harvesting complexes from extractions of spinach leaves índice de autoresíndice de materiabúsqueda de artículos
Home Pagelista alfabética de revistas  

Servicios Personalizados



Links relacionados

  • En proceso de indezaciónCitado por Google
  • En proceso de indezaciónSimilares en Google


South African Journal of Science

versión On-line ISSN 1996-7489


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.

        · texto en Inglés     · Inglés ( pdf )


Creative Commons License All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License