Special Issue--Human Behavioural and Physiological Biometry using Machine Learning

Important Dates:

June 30th, 2014: Paper submission deadline

September 15th, 2014: Paper acceptance notification

October 31th, 2014: Second submission (minor/majors revisions only)

December 15th, 2014: Final paper acceptance notification

Scope: Biometric data, which are acquired through sensing of human behavior or its physiological characteristics, represent a very rich source of information. Once these cannot be easily stolen or shared, they have been used successfully in a wide variety of applications. Hardware devices, that efficiently sensing the human activities and provide a large mass of high quality biometric data, are in constant and fast evolution. In this context, it is emergent the need of new developments and the improvement of methods and techniques to data analysis and knowledge discovery, since there are a lot of systems that can be built using the results from such analysis and discoveries. Among the techniques are those from Machine Learning area, which are feasible to deal with this kind of data. In order to compose this edition, scientific and industrial contributions, which highlight the state of art and state of the practice in Human Behavior and Physiological Biometry using Machine Learning, are expected.

Topics: For submission to this AIR special issue are expected contribution formatted as scientific and unpublished papers, which present relevant content about Machine Learning applied in the following topics (and correlated topics):

Biometry based on:

  • Fingerprint, hand shape, etc
  • Retina, iris, eye, face, aging effects
  • Speaker, speech (text independent, text dependent)
  • Body gesture, touch gesture
  • Signature
  • Biomedical signals (dental, heartbeat, EMG, ECG, EEG, EOG, etc)
  • DNA
  • others
  • Multimodal analysis, fusion and features extraction in biometrics systems
  • Complexity, scalability, usability of biometric solutions
  • Applications and case of studies
  • Human factors in biometrics systems
  • Biometric databases

Special Issue Editors:

  • Clodoaldo Aparecido de Moraes Lima, Ph.D.
  • Contact: c.lima@usp.br
  • Sarajane Marques Peres, Ph.D.
  • Contact: sarajane@usp.br


Artificial Intelligence Research

ISSN 1927-6974 (Print)   ISSN 1927-6982 (Online)

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