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

Yulia Bolotova, Vladimir Spitsyn

Результат исследований: Материалы для книги/типы отчетовМатериалы для конференции

4 Цитирования (Scopus)

Аннотация

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.

Язык оригиналаАнглийский
Название основной публикацииProceedings - 2012 7th International Forum on Strategic Technology, IFOST 2012
DOI
СостояниеОпубликовано - 2012
Событие2012 7th International Forum on Strategic Technology, IFOST 2012 - Tomsk, Российская Федерация
Продолжительность: 18 сен 201221 сен 2012

Другое

Другое2012 7th International Forum on Strategic Technology, IFOST 2012
СтранаРоссийская Федерация
ГородTomsk
Период18.9.1221.9.12

ASJC Scopus subject areas

  • Management of Technology and Innovation

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  • Цитировать

    Bolotova, Y., & Spitsyn, V. (2012). Analysis of hierarchically-temporal dependencies for handwritten symbols and gestures recognition. В Proceedings - 2012 7th International Forum on Strategic Technology, IFOST 2012 [6357628] https://doi.org/10.1109/IFOST.2012.6357628