Application of Numenta® Hierarchical Temporal Memory for land-use classification

Application of Numenta® Hierarchical Temporal Memory for land-use classification

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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...

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Main Authors: A.J. Perea, J.E. Meroño, M.J. Aguilera
Format: Article
Language:English
Published: Academy of Science of South Africa 2010-01-01
Series:South African Journal of Science
Online Access:http://192.168.0.121/index.php/sajs/article/view/10054
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spelling doaj-13019ce4451641b8ae1d87635e356ad12021-04-06T13:39:14ZengAcademy of Science of South AfricaSouth African Journal of Science1996-74892010-01-011059/10Application of Numenta® Hierarchical Temporal Memory for land-use classificationA.J. PereaJ.E. MeroñoM.J. Aguilera 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. http://192.168.0.121/index.php/sajs/article/view/10054
collection DOAJ
language English
format Article
sources DOAJ
author A.J. Perea
J.E. Meroño
M.J. Aguilera
spellingShingle A.J. Perea
J.E. Meroño
M.J. Aguilera
Application of Numenta® Hierarchical Temporal Memory for land-use classification
South African Journal of Science
author_facet A.J. Perea
J.E. Meroño
M.J. Aguilera
author_sort A.J. Perea
title Application of Numenta® Hierarchical Temporal Memory for land-use classification
title_short Application of Numenta® Hierarchical Temporal Memory for land-use classification
title_full Application of Numenta® Hierarchical Temporal Memory for land-use classification
title_fullStr Application of Numenta® Hierarchical Temporal Memory for land-use classification
title_full_unstemmed Application of Numenta® Hierarchical Temporal Memory for land-use classification
title_sort application of numenta® hierarchical temporal memory for land-use classification
publisher Academy of Science of South Africa
series South African Journal of Science
issn 1996-7489
publishDate 2010-01-01
description 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.
url http://192.168.0.121/index.php/sajs/article/view/10054
work_keys_str_mv AT ajperea applicationofnumentahierarchicaltemporalmemoryforlanduseclassification
AT jemerono applicationofnumentahierarchicaltemporalmemoryforlanduseclassification
AT mjaguilera applicationofnumentahierarchicaltemporalmemoryforlanduseclassification
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