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, Ensemble Methods, and so on, and exploit these novel 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

• Deep Face Detection

• Deep Gait Recognition

• Biometrics in Cybersecurity

• Biometrics in Cognitive Robot

• Healthcare Biometrics

• Medical Biometrics

• Biometrics in Social Computing

• Biometric Block Chain

• Privacy and Security Issues

• Iris, Fingerprints, DNA, Palmprints

• Gait, EEG, Heart rates

• Multimodal Fusion

• Soft Biometrics

• Cancellable Biometrics

• 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: as soon as possible

  Notification of initial editorial decisions: 2-3 days after abstract 
submission

  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

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


Editorial Board

• Dr Richard Jiang

   Computer and Information Sciences,

   Northumbria University, United Kingdom

   Email: richard.ji...@unn.ac.uk<mailto:richard.ji...@unn.ac.uk>

• Professor Chang-Tsun Li

   School of Computing and Mathematics,

   Charles Sturt University, Australia

   Email: c...@csu.edu.au<mailto:c...@csu.edu.au>

• Dr Weizhi Meng

   Applied Mathematics & Computer Science

   Technical University of Denmark, Denmark

   Email: w...@dtu.dk<mailto:w...@dtu.dk>

• Professor Christophe Rosenberger

   Computer Security

   ENSICAEN – GREYC, France

   Email: 
christophe.rosenber...@ensicaen.fr<mailto:christophe.rosenber...@ensicaen.fr>



Contact:

All questions about submissions can be emailed to 
perceptualscie...@outlook.com<mailto:perceptualscie...@outlook.com> or any 
editor in the board.



Many thanks!



Kind Regards,

Editors of the Book













































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