SciELO - Scientific Electronic Library Online

vol.105 issue9-10Experimental 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 author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand



Related links

  • On index processCited by Google
  • On index processSimilars in Google


South African Journal of Science

On-line version ISSN 1996-7489
Print version ISSN 0038-2353


PEREA, A.J.; MERONO, J.E.  and  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.

Keywords : memory-prediction theory; NuPIC®; UltraCamD® sensor; Hierarchical Temporal Memory.

        · text in English     · English ( pdf )


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