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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Academy of Science of South Africa
2010-01-01
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| Series: | South African Journal of Science |
| Online Access: | http://192.168.0.117/index.php/sajs/article/view/10054 |
| Summary: | 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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| ISSN: | 1996-7489 |