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Multipose Face Recognition-Based Combined Adaptive Deep Learning Vector Quantization
Joint Authors
Sarhan, Shahenda
Nasr, Aida A.
Shams, Mahmoud Y.
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-09-24
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Multipose face recognition system is one of the recent challenges faced by the researchers interested in security applications.
Different researches have been introduced discussing the accuracy improvement of multipose face recognition through enhancing the face detector as Viola-Jones, Real Adaboost, and Cascade Object Detector while others concentrated on the recognition systems as support vector machine and deep convolution neural networks.
In this paper, a combined adaptive deep learning vector quantization (CADLVQ) classifier is proposed.
The proposed classifier has boosted the weakness of the adaptive deep learning vector quantization classifiers through using the majority voting algorithm with the speeded up robust feature extractor.
Experimental results indicate that, the proposed classifier provided promising results in terms of sensitivity, specificity, precision, and accuracy compared to recent approaches in deep learning, statistical, and classical neural networks.
Finally, the comparison is empirically performed using confusion matrix to ensure the reliability and robustness of the proposed system compared to the state-of art.
American Psychological Association (APA)
Sarhan, Shahenda& Nasr, Aida A.& Shams, Mahmoud Y.. 2020. Multipose Face Recognition-Based Combined Adaptive Deep Learning Vector Quantization. Computational Intelligence and Neuroscience،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1138854
Modern Language Association (MLA)
Sarhan, Shahenda…[et al.]. Multipose Face Recognition-Based Combined Adaptive Deep Learning Vector Quantization. Computational Intelligence and Neuroscience No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1138854
American Medical Association (AMA)
Sarhan, Shahenda& Nasr, Aida A.& Shams, Mahmoud Y.. Multipose Face Recognition-Based Combined Adaptive Deep Learning Vector Quantization. Computational Intelligence and Neuroscience. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1138854
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1138854