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 and Data Labeling for Medical Applications
    sub title: First International Workshop, LABELS 2016, and Second International Workshop, DLMIA 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 21, 2016, Proceedings
  name:
    name part: Carneiro, Gustavo.
    role:
      role term: editor.
  name:
    name part: Mateus, Diana.
    role:
      role term: editor.
  name:
    name part: Peter, Loïc.
    role:
      role term: editor.
  name:
    name part: Bradley, Andrew.
    role:
      role term: editor.
  name:
    name part: Tavares, João Manuel R. S.
    role:
      role term: editor.
  name:
    name part: Belagiannis, Vasileios.
    role:
      role term: editor.
  name:
    name part: Papa, João Paulo.
    role:
      role term: editor.
  name:
    name part: Nascimento, Jacinto C.
    role:
      role term: editor.
  name:
    name part: Loog, Marco.
    role:
      role term: editor.
  name:
    name part: Lu, Zhi.
    role:
      role term: editor.
  name:
    name part: Cardoso, Jaime S.
    role:
      role term: editor.
  name:
    name part: Cornebise, Julien.
    role:
      role term: editor.
  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: XIII, 280 p. 115 illus. online resource.
  abstract: This book constitutes the refereed proceedings of two workshops held at the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, in Athens, Greece, in October 2016: the First Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2016, and the Second International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2016. The 28 revised regular papers presented in this book were carefully reviewed and selected from a total of 52 submissions. The 7 papers selected for LABELS deal with topics from the following fields: crowd-sourcing methods; active learning; transfer learning; semi-supervised learning; and modeling of label uncertainty. The 21 papers selected for DLMIA span a wide range of topics such as image description; medical imaging-based diagnosis; medical signal-based diagnosis; medical image reconstruction and model selection using deep learning techniques; meta-heuristic techniques for fine-tuning parameter in deep learning-based architectures; and applications based on deep learning techniques.
  table of contents: Active learning -- Semi-supervised learning -- Reinforcement learning -- Domain adaptation and transfer learning -- Crowd-sourcing annotations and fusion of labels from different sources -- Data augmentation -- Modelling of label uncertainty -- Visualization and human-computer interaction -- Image description -- Medical imaging-based diagnosis -- Medical signal-based diagnosis -- Medical image reconstruction and model selection using deep learning techniques -- Meta-heuristic techniques for fine-tuning -- Parameter in deep learning-based architectures -- Applications based on deep learning techniques.
  note: edited by Gustavo Carneiro, Diana Mateus, Loïc Peter, Andrew Bradley, João Manuel R. S. Tavares, Vasileios Belagiannis, João Paulo Papa, Jacinto C. Nascimento, Marco Loog, Zhi Lu, Jaime S. Cardoso, Julien Cornebise.
  subject:
    topic: Computer science
  subject:
    topic: Health informatics
  subject:
    topic: Artificial intelligence
  subject:
    topic: Computer graphics
  subject:
    topic: Image processing
  subject:
    topic: Pattern recognition
  subject:
    topic: Computer Science
  subject:
    topic: Image Processing and Computer Vision
  subject:
    topic: Pattern Recognition
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  subject:
    topic: Computer Graphics
  subject:
    topic: Health Informatics
  classification: TA1637-1638
  classification: TA1634
  classification: 006.6
  classification: 006.37
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Lecture Notes in Computer Science, 10008
  identifier: 9783319469768
  identifier: http://dx.doi.org/10.1007/978-3-319-46976-8
  record info:
    record creation date: 160926
    record change date: 20160926061853.0
    record identifier: 978-3-319-46976-8