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

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 2009-09-01
Series:South African Journal of Science
Online Access:https://sajs.co.za/article/view/10248
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author A.J. Perea
J.E. Meroño
M.J. Aguilera
author_facet A.J. Perea
J.E. Meroño
M.J. Aguilera
author_sort A.J. Perea
collection DOAJ
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.
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publishDate 2009-09-01
publisher Academy of Science of South Africa
record_format Article
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spelling doaj-art-c04ad7e021f943cc83f172bc68f1da142025-08-20T03:13:36ZengAcademy of Science of South AfricaSouth African Journal of Science1996-74892009-09-011059/108429Application of Numenta® Hierarchical Temporal Memory for land-use classificationA.J. PereaJ.E. MeroñoM.J. AguileraThe 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.https://sajs.co.za/article/view/10248
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
title 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_short Application of Numenta® Hierarchical Temporal Memory for land-use classification
title_sort application of numenta r hierarchical temporal memory for land use classification
url https://sajs.co.za/article/view/10248
work_keys_str_mv AT ajperea applicationofnumentahierarchicaltemporalmemoryforlanduseclassification
AT jemerono applicationofnumentahierarchicaltemporalmemoryforlanduseclassification
AT mjaguilera applicationofnumentahierarchicaltemporalmemoryforlanduseclassification