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Object Recognition Using Hierarchical Temporal Memory

  • Fabián Fallas-MoyaEmail author
  • Francisco Torres-Rojas
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 820)

Abstract

At this time, great effort is being directed toward developing problem-solving technology that mimic human cognitive processes. Research has been done to develop object recognition using Computer Vision for daily tasks such as secure access, traffic management, and robotic behavior. For this research, four different machine learning algorithms have been developed to overcome the computer vision problem of object recognition. Hierarchical temporal memory (HTM) is an emerging technology based on biological methods of the human cortex to learn patterns. This research applied an HTM algorithm to images (video sequences) in order to compare this technique against two others: support vector machines (SVM) and artificial neural networks (ANN). It was concluded that HTM was the most effective.

Keywords

Machine learning Computer vision HTM 

Notes

Acknowledgements

We would like to thank our colleagues from the Happy Few Research Group for their support during the development of this research. In addition, we thank the PARMA Group for its guidance and support publishing this research.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Universidad de Costa RicaCartagoCosta Rica
  2. 2.Instituto Tecnológico de Costa RicaCartagoCosta Rica

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