COMPARATIVE STUDY OF COMPUTATIONAL INTELLIGENCE PARADIGMS FOR INTELLIGENT ACCESS CONTROL BASED ON BIOMETRICS METHODOLOGIES

Shaymaa Adnan Abdulrahman
<span title="2020-08-18">2020</span> <i title="Journal of Mechanics of Continua and Mathematical Sciences"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/km45ab6gnrbt5o7ulvumvzqf34" style="color: black;">JOURNAL OF MECHANICS OF CONTINUA AND MATHEMATICAL SCIENCES</a> </i> &nbsp;
Intelligent access control is one of the challenging tasks in the human identification, image analysis, and diagnoses disease and computer vision. The focus towards the intelligent access control has been increased in the last years due to its various, applications in different domains. For this reason, it was used intelligent access control to facilitate the task of identifying the human. The objective of this paper is to analyse and evaluate the seven techniques for the intelligent access
more &raquo; ... rol and advantage and disadvantage of each type. In addition, represents biometrics characteristics in general. The Biometric feature is used to determine human identity including the brain signals. Through this study, brain signals are the best among the techniques. In this study, we first presented a survey of the Computational intelligence techniques in biometrics. All previous studies used brain EEG signals. Where different algorithms were used to extract, the features. These feature applied for human identification. The Accuracy achieved was up to 97% according to the studies found in this research.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.26782/jmcms.2020.08.00049">doi:10.26782/jmcms.2020.08.00049</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/67ciu4v2f5dlvagt56lybjnwcu">fatcat:67ciu4v2f5dlvagt56lybjnwcu</a> </span>
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