Bioinspired memory model for HTM face recognition

Olga Krestinskaya, Alex Pappachen James

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

1 Citation (Scopus)

Abstract

Inspired from the working principle of human memory, we propose a new algorithm for storing HTM features detected from images. The resulting features from the training set require lower memory than existing HTM training set. The proposed features are tested in a face recognition problem using the benchmark AR dataset. The simulation results show that the proposed algorithm gives higher face recognition accuracy, in comparison to the conventional methods.

Original languageEnglish
Title of host publication2016 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2016
EditorsJoel J. P. C. Rodrigues, Patrick Siarry, Gregorio Martinez Perez, Raghuvir Tomar, Al-Sakib Khan Pathan, Sameep Mehta, Sabu M. Thampi, Stefano Berretti, Ravi Prakash Gorthi, Al-Sakib Khan Pathan, Jinsong Wu, Jie Li, Vivek Jain, Joel J. P. C. Rodrigues, Mohammed Atiquzzaman, Joel J. P. C. Rodrigues, Punam Bedi, Mohamed Habib Kammoun
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1528-1532
Number of pages5
ISBN (Electronic)9781509020287
DOIs
Publication statusPublished - Nov 2 2016
Externally publishedYes
Event5th International Conference on Advances in Computing, Communications and Informatics, ICACCI 2016 - Jaipur, India
Duration: Sep 21 2016Sep 24 2016

Publication series

Name2016 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2016

Conference

Conference5th International Conference on Advances in Computing, Communications and Informatics, ICACCI 2016
CountryIndia
CityJaipur
Period9/21/169/24/16

ASJC Scopus subject areas

  • Information Systems
  • Computer Science (miscellaneous)
  • Computer Networks and Communications
  • Hardware and Architecture

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