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 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
Please feel free to contact us via email (perceptualscience@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.jiang@unn.ac.uk
• Dr Weizhi Meng
Applied Mathematics & Computer Science
Technical University of Denmark, Denmark
Email: weme@dtu.dk
• Professor Chang-Tsun Li
School of Computing and Mathematics,
Charles Sturt University, Australia
Email: chli@csu.edu.au
• Professor Christophe Rosenberger
Computer Security
ENSICAEN – GREYC, France
Email: christophe.rosenberger@ensicaen.fr

Contact:
All questions about submissions can be emailed to perceptualscience@outlook.com or any editor in the board.