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: Advances in Computer Vision
    sub title: Proceedings of the 2019 Computer Vision Conference (CVC), Volume 1
  name:
    name part: Arai, Kohei.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Kapoor, Supriya.
    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
  genre: Electronic books.
  origin info:
    place:
      place term: sz
    date issued: 2020
    edition: 1st ed. 2020.
    issuance: monographic
  language:
    language term: eng
  physical description:
    reformatting quality: access
    form: remote
    extent: 1 online resource (XII, 821 pages 513 illustrations, 359 illustrations in color.)
  abstract: This book presents a remarkable collection of chapters covering a wide range of topics in the areas of Computer Vision, both from theoretical and application perspectives. It gathers the proceedings of the Computer Vision Conference (CVC 2019), held in Las Vegas, USA from May 2 to 3, 2019. The conference attracted a total of 371 submissions from pioneering researchers, scientists, industrial engineers, and students all around the world. These submissions underwent a double-blind peer review process, after which 120 (including 7 poster papers) were selected for inclusion in these proceedings. The book's goal is to reflect the intellectual breadth and depth of current research on computer vision, from classical to intelligent scope. Accordingly, its respective chapters address state-of-the-art intelligent methods and techniques for solving real-world problems, while also outlining future research directions. Topic areas covered include Machine Vision and Learning, Data Science, Image Processing, Deep Learning, and Computer Vision Applications.
  table of contents: Deep Learning for Detection of Railway Signs and Signals -- 3D Conceptual Design using Deep Learning -- The Effect of Color Channel Representations on the Transferability of Convolutional Neural Networks -- Weakly Supervised Deep Metric Learning for Template Matching -- Deep Learning vs. Traditional Computer Vision -- Deep Cross-modal Age Estimation -- No-reference Image Denoising Quality Assessment -- Plant Leaf Disease Detection using Adaptive Neuro-Fuzzy Classification -- Fusion of CNN- and COSFIRE-based Features with Application to Gender Recognition from Face Images -- Learning of Shape Models from Exemplars of Biological Objects in Images -- Researcher Profile Ontology for Academic Environment.
  note: edited by Kohei Arai, Supriya Kapoor.
  subject:
    topic: Computational intelligence
  subject:
    topic: Artificial intelligence
  subject:
    topic: Optical data processing
  subject:
    topic: Computational Intelligence
  subject:
    topic: Artificial Intelligence
  subject:
    topic: Image Processing and Computer Vision
  classification: Q342
  classification: 006.3
  related item:
    title info:
      title: Springer Nature eBook
  related item:
    title info:
      title: Advances in Intelligent Systems and Computing, 943
  identifier: 9783030177959
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record creation date: 190423
    record change date: 20230330185227.0
    record identifier: in00004428238