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: Applications of Evolutionary Computation in Image Processing and Pattern Recognition
  name:
    name part: Cuevas, Erik.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Zaldívar, Daniel.
    role:
      role term: author.
  name:
    name part: Perez-Cisneros, Marco.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2016
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XV, 274 p. 111 illus., 55 illus. in color. online resource.
  abstract: This book presents the use of efficient Evolutionary Computation (EC) algorithms for solving diverse real-world image processing and pattern recognition problems. It provides an overview of the different aspects of evolutionary methods in order to enable the reader in reaching a global understanding of the field and, in conducting studies on specific evolutionary techniques that are related to applications in image processing and pattern recognition. It explains the basic ideas of the proposed applications in a way that can also be understood by readers outside of the field. Image processing and pattern recognition practitioners who are not evolutionary computation researchers will appreciate the discussed techniques beyond simple theoretical tools since they have been adapted to solve significant problems that commonly arise on such areas. On the other hand, members of the evolutionary computation community can learn the way in which image processing and pattern recognition problems can be translated into an optimization task. The book has been structured so that each chapter can be read independently from the others. It can serve as reference book for students and researchers with basic knowledge in image processing and EC methods.
  table of contents: Introduction -- Image Segmentation Based on Differential Evolution Optimization.-Motion Estimation Based on Artificial Bee Colony (ABC) -- Ellipse Detection on Images Inspired by the Collective Animal Behavior -- Template Matching by Using the States of Matter Algorithm -- Estimation of Multiple View Relations Considering Evolutionary Approaches -- Circle Detection on Images Based on an Evolutionary Algorithm that Reduces the Number of Function Evaluations -- Otsu and Kapur Segmentation Based on Harmony Search Optimization -- Leukocyte Detection by Using Electromagnetism-Like Optimization -- Automatic Segmentation by Using an Algorithm Based on the Behavior of Locust Swarms.
  note: by Erik Cuevas, Daniel Zaldívar, Marco Perez-Cisneros.
  subject:
    topic: Engineering
  subject:
    topic: Artificial intelligence
  subject:
    topic: Image processing
  subject:
    topic: Calculus of variations
  subject:
    topic: Computational intelligence
  subject:
    topic: Engineering
  subject:
    topic: Computational Intelligence
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  subject:
    topic: Signal, Image and Speech Processing
  subject:
    topic: Image Processing and Computer Vision
  subject:
    topic: Calculus of Variations and Optimal Control; Optimization
  classification: Q342
  classification: 006.3
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Intelligent Systems Reference Library, 100
  identifier: 9783319264622
  identifier: http://dx.doi.org/10.1007/978-3-319-26462-2
  record info:
    record creation date: 151107
    record change date: 20170519222232.0
    record identifier: 978-3-319-26462-2