Research Article
Open access
Published on 15 March 2024
Download pdf
Yang,W. (2024). Research on algorithm accuracy and the application of facial recognition technologies. Applied and Computational Engineering,46,273-277.
Export citation

Research on algorithm accuracy and the application of facial recognition technologies

Wenjie Yang *,1,
  • 1 University of Glasgow

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/46/20241553

Abstract

Research on face recognition systems began in the 1960s. It is a biometric technology that is based on some features as well as areas of the face for recognition. After collecting the images with the help of model acquisition, algorithms are used to process the recognized images. Nowadays, face recognition technology is being used all around people's lives and is very relevant to people's lives. The article will introduce the use of face recognition technology in different fields. It submits the application of face recognition in different backgrounds and application scenarios. It will introduce some representative applications, and analyse the implementation of the core algorithm of the technology, and the results. The paper will also provide a dialectical discussion of face recognition to gain a deeper understanding of the technology. Face recognition has become one of the most popular technologies nowadays and has a great prospect in the future.

Keywords

Face recognition technology, algorithms accuracy, image recognition

[1]. Adjabi I, Ouahabi A, Benzaoui A, Taleb-Ahmed A 2020 Past, present, and future of face recognition: A review Electronics 9 8 1188

[2]. Li L, Mu X, Li S, Peng H 2020 A review of face recognition technology IEEE Access 8 139110-139120

[3]. El Naqa I, Murphy M J 2015 What is machine learning? Springer International Publishing 3-11

[4]. Shah N, Bhagat N, Shah M 2021 Crime forecasting: a machine learning and computer vision approach to crime prediction and prevention Visual Computing for Industry, Biomedicine, and Art 4 1-14

[5]. Li L, Mu X, Li S, Peng H 2020 A review of face recognition technology IEEE Access 8 139110-139120

[6]. Bansal A, Mehta K, Arora S 2012 Face recognition using PCA and LDA algorithm In 2012 second international conference on Advanced Computing & Communication Technologies 251-254

[7]. Wang D, Yu H, Wang D, Li G 2020 Face recognition system based on CNN In 2020 International Conference on Computer Information and Big Data Applications (CIBDA) 470-473

[8]. Jacob J E, Saritha S 2021 Video Enhancement and Low-Resolution Facial Image Reconstruction for Crime Investigation In Intelligent Data Communication Technologies and Internet of Things: Proceedings of ICICI 2020 773-788

[9]. Ratnaparkhi S T, Tandasi A, Saraswat S 2021 Face detection and recognition for criminal identification system In 2021 11th International Conference on Cloud Computing, Data Science & Engineering (Confluence) 773-777

[10]. Mahmood Z, Ali T, Khattak S, Hasan L, Khan S U 2015 Automatic player detection and identification for sports entertainment applications Pattern Analysis and Applications 18 971-982

[11]. Cosentino S, Randria E I, Lin J Y, Pellegrini T, Sessa S, Takanishi A 2018 Group emotion recognition strategies for entertainment robots In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 813-818

[12]. Vishnuvardhan G, Ravi V 2021 Face recognition using transfer learning on facenet: Application to banking operations In Modern Approaches in Machine Learning and Cognitive Science: A Walkthrough: Latest Trends in AI 2 301-309

[13]. Chen Q, Sang L 2018 Face-mask recognition for fraud prevention using Gaussian mixture model Journal of Visual Communication and Image Representation 55 795-801

Cite this article

Yang,W. (2024). Research on algorithm accuracy and the application of facial recognition technologies. Applied and Computational Engineering,46,273-277.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

Disclaimer/Publisher's Note

The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of EWA Publishing and/or the editor(s). EWA Publishing and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

About volume

Volume title: Proceedings of the 4th International Conference on Signal Processing and Machine Learning

Conference website: https://www.confspml.org/
ISBN:978-1-83558-333-3(Print) / 978-1-83558-334-0(Online)
Conference date: 15 January 2024
Editor:Marwan Omar
Series: Applied and Computational Engineering
Volume number: Vol.46
ISSN:2755-2721(Print) / 2755-273X(Online)

© 2024 by the author(s). Licensee EWA Publishing, Oxford, UK. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. Authors who publish this series agree to the following terms:
1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this series.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this series.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See Open access policy for details).