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: Deep Learning in Object Detection and Recognition
  name:
    name part: Jiang, Xiaoyue.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Hadid, Abdenour.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Pang, Yanwei.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Granger, Eric.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Feng, Xiaoyi.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: si
    date issued: 2019
    edition: 1st ed. 2019.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XVI, 224 p. 113 illus., 92 illus. in color. online resource.
  abstract: This book discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing. It provides a systematic and methodical overview of the latest developments in deep learning theory and its applications to computer vision, illustrating them using key topics, including object detection, face analysis, 3D object recognition, and image retrieval. The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in deep learning, computer vision and beyond and can also be used as a reference book. The comprehensive comparison of various deep-learning applications helps readers with a basic understanding of machine learning and calculus grasp the theories and inspires applications in other computer vision tasks.
  table of contents: 1. An Overview of Deep Learning -- 2. Object Detection In Deep Learning -- 3. Deep Learning in Face Recognition across Pose and Illumination -- 4. Face Anti-spoofing via Deep Local Binary Pattern -- 5. Face Anti-spoofing via Deep Local Binary Pattern -- 6. Deep Learning Architectures for Face Recognition in Video Surveillance -- 7. Deep learning for 3D data -- 8. Deep Learning based Descriptors for Object Instance Search.
  note: edited by Xiaoyue Jiang, Abdenour Hadid, Yanwei Pang, Eric Granger, Xiaoyi Feng.
  subject:
    topic: Optical data processing
  subject:
    topic: Data mining
  subject:
    topic: Pattern recognition
  subject:
    topic: Image Processing and Computer Vision
  subject:
    topic: Data Mining and Knowledge Discovery
  subject:
    topic: Pattern Recognition
  classification: TA1630-1650
  classification: 006.6
  classification: 006.37
  related item:
    title info:
      title: Springer eBooks
  identifier: 9789811051524
  identifier: https://doi.org/10.1007/978-981-10-5152-4
  record info:
    record creation date: 191118
    record change date: 20191220130530.0
    record identifier: 978-981-10-5152-4