[visionlist] Call for Book Chapters on Deep Biometrics

[Richard Jiang]

Dear Colleagues,

We would like to invite you to contribute a chapter for the upcoming volume entitled Deep Biometrics to be published by Springer, the largest global scientific, technical, and medical ebook publisher. The volume will be available both in print and in ebook format by late 2018/early 2019 on SpringerLink, one of the leading science portals that includes more than 8 million documents, an ebook collection with more than 160,000 titles, journal archives digitized back to the first issues in the 1840s, and more than 30,000 protocols and 290 reference works.

Below is a short description of the volume:

Recent development in machine learning, particularly deep learning, has brought out drastic impact on Biometrics, which is a classic topic to utilize Machine Learning for biometric identification. Particularly, Deep Learning can benefit from the training with large unlabelled datasets via semi-supervised or unsupervised learning.

This book aims to highlight recent research advances in biometrics using semi-supervised and unsupervised new methods such as Deep Neural Networks, Deep Stacked Autoencoder, Convolutional Neural Networks, Generative Adversary Networks, and so on, and exploit these new methods in the emerging new areas such as privacy and security issues, cancellable biometrics and soft biometrics, smart cities, big biometric data, biometric banking, medical biometrics, and healthcare biometrics, etc..

The goal of this volume is to summarize the recent advances in using Deep Learning in the area of biometric security and privacy. Topics of interest include: (but not limited to)

• Deep Learned Biometric Features
• Convolutional Neural networks
• Deep Stacked Autoencoder
• Biometrics in Cybersecurity
• Biometrics in Cognitive Robot
• Healthcare Biometrics
• Medical Biometrics
• Biometrics in Social Computing
• Privacy and Security Issues
• Deep Face Detection
• Deep Face Recognition
• Iris, Fingerprints, DNA, Palmprints
• Gait, EEG, Heart rates
• Multimodal Fusion
• Soft Biometrics
• Cancellable Biometrics with Deep Learning
• Big data issues in Biometrics
• Biometrics for Internet of things

Each contributed chapter is expected to present a novel research study, a comparative study, or a survey of the literature. Note that there will be no publication fees for accepted chapters.


Important Dates

Submission of abstracts Nov 15, 2018
Notification of initial editorial decisions Nov 20, 2018
Submission of full-length chapters Dec 15, 2018
Notification of final editorial decisions Jan 15, 2019
Submission of revised chapters Feb 15, 2019


All submissions should be done via EasyChair:

  https://easychair.org/conferences/?conf=deepbio2019

Original artwork and a signed copyright release form will be required for all accepted chapters. For author instructions, please visit:

  http://www.springer.com/authors/book+authors?SGWID=0-154102-12-417900-0<http://www.google.com/url?q=http%3A%2F%2Fwww.springer.com%2Fauthors%2Fbook%2Bauthors%3FSGWID%3D0-154102-12-417900-0&sa=D&sntz=1&usg=AFQjCNHN0YBP4u2cmYXIB6_4J17BG8OFCg>

Please feel free to contact us via email (perceptualscience at outlook.com<mailto:perceptualscience at outlook.com>, or any editors below) regarding your chapter ideas.



Editorial Board

  *   Dr Richard Jiang
Computer and Information Sciences,
Northumbria University, United Kingdom
Web: http://bit.ly/2n5glEx
  *   Dr Weizhi Meng
Applied Mathematics & Computer Science
Technical University of Denmark, Denmark
  *   Professor Chang-Tsun Li
School of Computing and Mathematics,
Charles Sturt University, Australia
  *   Professor Christophe Rosenberger
Computer Security
ENSICAEN – GREYC, France

Contact

All questions about submissions can be emailed to Dr Richard Jiang (perceptualscience at outlook.com<mailto:perceptualscience at outlook.com>, or richard.jiang at unn.ac.uk<mailto:richard.jiang at unn.ac.uk>).

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