Proposed Face Recognition System Based on Immune Inspired Anomaly Detection Using Symbiotic Agents

Ruan Spijkerman, Elizabeth Ehlers

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper proposes the design of a face recognition system based on immune inspired anomaly detection using intelligent agents with symbiotic relationships. Based on the reviewed literature, the advantages of the aforementioned technologies will synergise to create an effective system in scenarios where a person's details are not as important as maintaining a current representation of their face and detecting anomalous individuals. The paper discusses the working of the individual agents and their symbiotic relationships in the proposed model. Two example scenarios illustrate how the proposed system may be implemented to take advantage of the characteristics of immune inspired anomaly detection.

Original languageEnglish
Title of host publicationCIIS 2021 - 2021 4th International Conference on Computational Intelligence and Intelligent Systems
PublisherAssociation for Computing Machinery
Pages19-24
Number of pages6
ISBN (Electronic)9781450385930
DOIs
Publication statusPublished - 20 Nov 2021
Event4th International Conference on Computational Intelligence and Intelligent Systems, CIIS 2021 - Virtual, Online, Japan
Duration: 20 Nov 202122 Nov 2021

Publication series

NameACM International Conference Proceeding Series

Conference

Conference4th International Conference on Computational Intelligence and Intelligent Systems, CIIS 2021
Country/TerritoryJapan
CityVirtual, Online
Period20/11/2122/11/21

Keywords

  • Anomaly Detection
  • Face Recognition
  • Immune Inspired Computation
  • Symbiotic Agents

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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