Special Issue "Deep Learning-Based Biometric Technologies"
A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer Science and Symmetry/Asymmetry".
Deadline for manuscript submissions: closed (31 August 2019) | Viewed by 31604
Special Issue Editors
Interests: deep learning; biometrics; image processing
Special Issues, Collections and Topics in MDPI journals
Interests: discrete geometry analysis; 3D face recognition; 3D facial expression analysis; deep learning for 3D shapes
Special Issue Information
Dear Colleagues,
Recent developments have led to the widespread use of biometric technologies, such as face, fingerprint, vein, iris, palmprint, wrinkle, voice, and gait recognition, in a variety of applications in access control, financial transactions on mobile devices, and automatic teller machines (ATMs). While existing biometric technology has matured, its performance is still affected by various environmental conditions, and recent approaches have been attempted to combine deep learning techniques with conventional biometrics to guarantee the higher performance. The objective of this Special Issue is to invite high-quality, state-of-the-art research papers that deal with challenging issues in deep learning-based biometric technologies. We solicit the original papers of unpublished and completed research that are not currently under review by any other conference/magazine/journal. Topics of interest include, but are not limited to:
- Region of interest (ROI) or feature point detection for biometrics based on deep learning
- Biometric feature extraction based on deep learning
- Biometric recognition based on deep learning
- Soft biometrics based on deep learning
- Multimodal biometrics based on deep learning
- Spoof detection based on deep learning
Prof. Kang Ryoung Park
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Symmetry is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- Region of interest (ROI) or feature point detection for biometrics based on deep learning
- Biometric feature extraction based on deep learning
- Biometric recognition based on deep learning
- Soft biometrics based on deep learning
- Multimodal biometrics based on deep learning
- Spoof detection based on deep learning