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Journal of Ambient Intelligence and Humanized Computing - Call for Papers: Biometric Security in the Pandemic and Artificial Intelligence Era

CLOSED FOR SUBMISSIONS


Biometrics can be defined as a technology which recognizes individuals by their physical or behavioral characteristics. This common definition is often employed by considering Biometrics as a security solution to deal with the identification or verification of individuals. Nowadays, Biometric technology is not restricted to law enforcement or government departments by identifying criminals or by controlling borders, but it is also accessible and used in almost everyday life. It allows a more secure access as well as making our life easier. Because Biometric systems are commonly integrated into general purpose devices such as smartphones and computers, the attitude of the public has changed towards them because it has become more acceptable. In addition, the commercial Biometric industry is still growing and is continually being innovated, so it is not surprising the conventional metal key and passwords will not be used anymore as we know it today.

The COVID-19 pandemic has considerably impacted our habits and daily lifestyle. Indeed, a range of various measures and restrictions have been implemented to control the new infections and reduce the pressure on the health care system. Among the adopted measures we can find enhanced hand hygiene, and mandatory mask-wearing. These measures represent a big challenge for the existing reliable biometric recognition systems including face, voice, and hand. Due to the previously mentioned challenges and the large development of artificial intelligence new opportunities and research directions can emerge such as touch-less fingerprint/palmprint, vein-based, gait, etc.

The aim of the proposed Special Issue is to promote research and reflect the most recent advances in biometric security in the pandemic and artificial intelligence era.

Topics of Interest
The topics of interest for this SI include, but are not limited to:

  • Touchless based biometrics
  • Vein based biometrics
  • Behavior based biometrics
  • Masked face-based biometrics
  • Artificial Intelligence for biometrics
  • Machine learning for biometrics
  • Deep learning for biometrics
  • Presentation attack detection
  • Adversarial attack detection 


Keywords:

  • Security
  • Biometrics
  • Identification
  • COVID-19
  • Artificial Intelligence
  • Machine learning
  • Deep learning

The format for the full article submission is available at: https://www.springer.com/journal/12652/submission-guidelines (this opens in a new tab)

GUEST EDITORS:

Dr. Imad Rida (Lead Guest Editor)
Associate Professor
University of Technology of Compiegne, France
Email: imad.rida@utc.fr (this opens in a new tab)

Imad Rida received the M.Sc. degree in Biometrics from Paris XII university and the Ph.D. degree in machine learning from INSA Rouen Normandie, France, in 2012 and 2017 respectively. In 2013, he was a research engineer at INRIA Sophia Antipolis (France). He was also a postdoctoral research fellow with the University of Qatar and National Higher French Institute of Aeronautics and Space, Toulouse (France). Since 2019, he has been an Associate Professor with the University of Technology of Compiègne, Compiègne (France). His research interests include machine learning, biometrics, pattern recognition, and signal/ image processing. He received the Brain Machine Interface - Best Paper Award - at IEEE SMC 2019. He serves/served as guest editor at Elsevier Engineering Applications of Artificial Intelligence, Elsevier Pattern Recognition Letters, Elsevier Innovation and Research in BioMedical engineering, IET Biometrics, MDPI Sensors, MDPI Electronics. He also acts as referee for international journals and conferences on machine learning, biometrics, pattern recognition and signal/image processing. He is an IEEE member and IAPR member. 

Dr. Paola Barra
Assistant Professor
Parthenope University of Naples, Italy
Email: paola.barra@uniparthenope.it (this opens in a new tab)

Paola Barra received the B.S. degree in computer science from the University of Salerno, the M.S. in business informatics from the university of Pisa, the Ph.D. degree from the University of Salerno in 2021. Her research interests include machine learning techniques to solve issues using computer vision, as facial and gait recognition, action recognition, tumor detection and image segmentation for litter deception and for reconstruction of the frescoes. She is a member of GIRPR/IAPR and now is an Assistant Professor in Computer Science at the University of Naples Parthenope, Italy. 

Dr. Angelo Gaeta
Assistant Professor
University of Salerno, Italy
Email: agaeta@unisa.it (this opens in a new tab)

Angelo Gaeta graduated with honors in Electronic Engineering from the University of Salerno and earned a Ph.D. in Management and Information Technology - Curriculum c) Information Security and Intelligent Systems - at the Department of Management & Innovation Systems (DISA-MIS) of the University of Salerno with Excellent rating. He is currently an Assistant professor (RTDB) in Computer Science at the University of Salerno and his main interests relate to Computational Intelligence and Approximate Reasoning Methods for decision-making, Big Data Analytics, Cognitive systems, Cloud Computing, Technology Enhanced Learning, Enterprise Knowledge Management. He is a co-author of over 50 scientific publications on these topics and serves as an associated editor of the Journal of Ambient Intelligence and Humanized Computing (JAIHC). 

Dr. Naser Damer
Senior Researcher
Fraunhofer Institute for Computer Graphics Research IGD, Germany
Email: naser.damer@igd.fraunhofer.de (this opens in a new tab)

Naser Damer received the Ph.D. degree in computer science from TU Darmstadt in 2018. He is a Senior Researcher with Fraunhofer IGD, performing research management, applied research, scientific consulting, and system evaluation. His main research interests lie in the fields of biometrics, machine learning, and information fusion. He is a Research Area Coordinator and a Principal Investigator with the National Research Center for Applied Cybersecurity ATHENE, Germany. He lectures on human and identity-centric machine learning, as well as on ambient intelligence with TU Darmstadt. He is a member of the organizing teams of several conferences, workshops, and special sessions, including being a Program Co-Chair of BIOSIG. He serves as an Associate Editor for Pattern Recognition (Elsevier) and the Visual Computer (Springer). He represents the German Institute for Standardization (DIN) in the ISO/IEC SC37 International Biometrics Standardization Committee. He is a member of the IEEE Biometrics Council serving on its Technical Activities Committee.


  • Opening date: March 22, 2023
  • Closure date:  November 30, 2023




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