Memristive threshold logic face recognition

Akshay Kumar Maan, Dinesh S. Kumar, Alex Pappachen James

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

6 Citations (Scopus)

Abstract

This paper presents a face recognition method implemented using reconfigurable network of memristive threshold logic cells that can be practically realised in a secondary plane to the pixel arrays. Among the most distinguishing features of the presented system are a) an early detection and storage of only the relevant information directly from the sensors, b) a parallel, scalable information storage and detection architecture in hardware, as opposed to an algorithmic approach, and c) a fast and robust face recognition system. The threshold logic cell is inspired from a simplistic cortical neuron model that has multiple inputs with corresponding input memristors and one binary output. These cells when used with a set of input memristors are able to detect significant pixel variations in the incoming video frame and memorize the output template depending on the logic of selection of the resistor values. The implemented face recognition circuit shows small chip area, low power dissipation and ability to scale the networks with increase in image resolutions.

Original languageEnglish
Title of host publication5th Annual International Conference on Biologically Inspired Cognitive Architectures, BICA 2014
PublisherElsevier
Pages98-103
Number of pages6
Volume41
DOIs
Publication statusPublished - 2014
Event5th Annual International Conference on Biologically Inspired Cognitive Architectures, BICA 2014 - Cambridge, United States
Duration: Nov 7 2014Nov 9 2014

Other

Other5th Annual International Conference on Biologically Inspired Cognitive Architectures, BICA 2014
CountryUnited States
CityCambridge
Period11/7/1411/9/14

Fingerprint

Threshold logic
Face recognition
Memristors
Pixels
Image resolution
Resistors
Computer hardware
Neurons
Energy dissipation
Data storage equipment
Networks (circuits)
Sensors

Keywords

  • Memristors
  • Object detection
  • Resistance networks
  • Threshold logic

ASJC Scopus subject areas

  • Computer Science(all)

Cite this

Maan, A. K., Kumar, D. S., & James, A. P. (2014). Memristive threshold logic face recognition. In 5th Annual International Conference on Biologically Inspired Cognitive Architectures, BICA 2014 (Vol. 41, pp. 98-103). Elsevier. https://doi.org/10.1016/j.procs.2014.11.090

Memristive threshold logic face recognition. / Maan, Akshay Kumar; Kumar, Dinesh S.; James, Alex Pappachen.

5th Annual International Conference on Biologically Inspired Cognitive Architectures, BICA 2014. Vol. 41 Elsevier, 2014. p. 98-103.

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

Maan, AK, Kumar, DS & James, AP 2014, Memristive threshold logic face recognition. in 5th Annual International Conference on Biologically Inspired Cognitive Architectures, BICA 2014. vol. 41, Elsevier, pp. 98-103, 5th Annual International Conference on Biologically Inspired Cognitive Architectures, BICA 2014, Cambridge, United States, 11/7/14. https://doi.org/10.1016/j.procs.2014.11.090
Maan AK, Kumar DS, James AP. Memristive threshold logic face recognition. In 5th Annual International Conference on Biologically Inspired Cognitive Architectures, BICA 2014. Vol. 41. Elsevier. 2014. p. 98-103 https://doi.org/10.1016/j.procs.2014.11.090
Maan, Akshay Kumar ; Kumar, Dinesh S. ; James, Alex Pappachen. / Memristive threshold logic face recognition. 5th Annual International Conference on Biologically Inspired Cognitive Architectures, BICA 2014. Vol. 41 Elsevier, 2014. pp. 98-103
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