Call of Papers for IEEE Access Special Issue on 4D's of ML in Biometrics

Call of Papers for IEEE Access Special Issue on 4D's of ML in Biometrics

4D's of Machine Learning for Biometrics: Deep Learning, Dictionary
Learning, Domain Adaptation, and Distance Metric Learning

1. Special Issue in IEEE Access (August 1, 2015)
2. Special Session in IEEE BTAS, 2015 (April 1, 2015)

With the availability of inexpensive biometric sensors, computing
power, and memory, it is becoming increasingly clear that biometrics
technology will have broader usage, and therefore also broader scope
of future research in addressing newer challenges and pushing the
boundaries. If we perceive biometrics as a fundamental problem in
science and engineering with broad economic and scientific impact,
then designing efficient algorithms and systems will require a
multidisciplinary effort in signal processing, pattern recognition,
machine learning, sensor design, embedded systems, and information
fusion. Recent advances in machine learning have seen widespread
development of algorithms in four specific areas: deep learning,
dictionary learning, domain adaptation, and distance metric learning.
As a consumer of these 4-D paradigms, the likelihood of exploring new
avenues of research is immense. Special issue in IEEE Access and
BTAS2015 special session focus on bringing together researchers and
practitioners in biometrics and machine learning to showcase the
progress, algorithms, and applications of deep learning, dictionary
learning, domain adaptation, and distance metric learning in
biometrics. Topics include, but not necessarily limited to:

- Novel feature representation using deep learning, dictionary
learning for face, fingerprint, ocular, and/or other biometric
modalities

- Novel algorithms for heterogeneous biometric recognition such as (a)
matching visible images to near-infrared images, (b) matching
cross-resolution images, and (c) matching sketches with digital face
images

- Novel algorithms for transferring knowledge from one biometric
domain to another, including transfer learning and other
semi-supervised learning algorithms

- Novel distance metric learning algorithms for biometrics modalities

- Applications of these paradigms in biometric systems

More details, including submission details and deadlines are available
at: https://research.iiitd.edu.in/groups/iab/cfp_4D.html