International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 129 - Issue 16 |
Published: November 2015 |
Authors: Fatemeh Asgari, Ali Salehi |
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Fatemeh Asgari, Ali Salehi . The biologically inspired Hierarchical Temporal Memory Model for Farsi Handwritten Digit and Letter Recognition. International Journal of Computer Applications. 129, 16 (November 2015), 6-11. DOI=10.5120/ijca2015906880
@article{ 10.5120/ijca2015906880, author = { Fatemeh Asgari,Ali Salehi }, title = { The biologically inspired Hierarchical Temporal Memory Model for Farsi Handwritten Digit and Letter Recognition }, journal = { International Journal of Computer Applications }, year = { 2015 }, volume = { 129 }, number = { 16 }, pages = { 6-11 }, doi = { 10.5120/ijca2015906880 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2015 %A Fatemeh Asgari %A Ali Salehi %T The biologically inspired Hierarchical Temporal Memory Model for Farsi Handwritten Digit and Letter Recognition%T %J International Journal of Computer Applications %V 129 %N 16 %P 6-11 %R 10.5120/ijca2015906880 %I Foundation of Computer Science (FCS), NY, USA
It is herein proposed a handwritten digit recognition system which biologically inspired of the large-scale structure of the mammalian neocortex. Hierarchical Temporal Memory (HTM) is a memory-prediction network model that takes advantage of the Bayesian belief propagation and revision techniques. In this article a study has been conducted to train a HTM network to recognize handwritten digits and letters taken from the well-known Hoda dataset for Farsi handwritten digit. Results presented in this paper show good performance and generalization capacity of the proposed network for a real-world big dataset.