Analysis of hierarchically-temporal dependencies for handwritten symbols and gestures recognition

Yulia Bolotova, Vladimir Spitsyn

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

This work represents a biologically inspired approach to object recognition based on analysis of hierarchical and temporal data dependencies. The article describes the hierarchical temporal memory model (HTM) and its optimization for object recognition task. Optimization includes Gabor and Canny filter image preprocessing, which makes the model suitable for handwritten symbols and gestures recognition; using of additional clustering on the stage of spatial pooling, a new proposed temporal grouping algorithm increases the overall recognition accuracy of the model; a new genetic algorithm was designed for searching the optimal parameters of the model.

Original languageEnglish
Title of host publicationProceedings - 2012 7th International Forum on Strategic Technology, IFOST 2012
DOIs
Publication statusPublished - 2012
Event2012 7th International Forum on Strategic Technology, IFOST 2012 - Tomsk, Russian Federation
Duration: 18 Sep 201221 Sep 2012

Other

Other2012 7th International Forum on Strategic Technology, IFOST 2012
CountryRussian Federation
CityTomsk
Period18.9.1221.9.12

Keywords

  • gesture recognition
  • hierarchical temporal memory
  • symbols recognition
  • temporal grouping

ASJC Scopus subject areas

  • Management of Technology and Innovation

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