rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Adaptive Biometric Systems
    sub title: Recent Advances and Challenges
  name:
    name part: Rattani, Ajita.
    role:
      role term: editor.
  name:
    name part: Roli, Fabio.
    role:
      role term: editor.
  name:
    name part: Granger, Eric.
    role:
      role term: editor.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2015
    edition: 1st ed. 2015.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: X, 134 p. 44 illus., 24 illus. in color. online resource.
  abstract: This timely and interdisciplinary volume presents a detailed overview of the latest advances and challenges remaining in the field of adaptive biometric systems. A broad range of techniques are provided from an international selection of pre-eminent authorities, collected together under a unified taxonomy and designed to be applicable to any pattern recognition system. Topics and features: Presents a thorough introduction to the concept of adaptive biometric systems, detailing their taxonomy, levels of adaptation, and open issues and challenges Reviews systems for adaptive face recognition that perform self-updating of facial models using operational (unlabeled) data Describes a novel semi-supervised training strategy known as fusion-based co-training Examines the characterization and recognition of human gestures in videos Discusses a selection of learning techniques that can be applied to build an adaptive biometric system Investigates procedures for handling temporal variance in facial biometrics due to aging Proposes a score-level fusion scheme for an adaptive multimodal biometric system This comprehensive text/reference will be of great interest to researchers and practitioners engaged in systems science, information security or biometrics. Postgraduate and final-year undergraduate students of computer engineering will also appreciate the coverage of intelligent and adaptive schemes for cutting-edge pattern recognition and signal processing in changing environments.
  note: edited by Ajita Rattani, Fabio Roli, Eric Granger.
  subject:
    topic: Computer science
  subject:
    topic: Artificial intelligence
  subject:
    topic: Pattern recognition
  subject:
    topic: Biometrics (Biology)
  subject:
    topic: Computer Science
  subject:
    topic: Biometrics
  subject:
    topic: Pattern Recognition
  subject:
    topic: Signal, Image and Speech Processing
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  classification: QH323.5
  classification: 570.15195
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Advances in Computer Vision and Pattern Recognition
  identifier: 9783319248653
  identifier: http://dx.doi.org/10.1007/978-3-319-24865-3
  record info:
    record creation date: 151022
    record change date: 20151204152246.0
    record identifier: 978-3-319-24865-3