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: Driver drowsiness detection
    sub title: systems and solutions
  name:
    name part: Čolić, Aleksandar
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Marques, Oge
    role:
      role term: author.
  name:
    name part: Furht, Borivoje
    role:
      role term: author.
  name:
    name part: EBSCOhost
  type of resource: text
  genre: bibliography
  genre: Electronic books.
  origin info:
    place:
      place term: sz
    date issued: 2014
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (ix, 50 pages) : illustrations (some color).
  abstract: This SpringerBrief presents the fundamentals of driver drowsiness detection systems, provides examples of existing products, and offers guides for practitioners interested in developing their own solutions to the problem. Driver drowsiness causes approximately 7% of all road accidents and up to 18% of fatal collisions. Proactive systems that are capable of preventing the loss of lives combine techniques, methods, and algorithms from many fields of engineering and computer science such as sensor design, image processing, computer vision, mobile application development, and machine learning which is covered in this brief. The major concepts addressed in this brief are: the need for such systems, the different methods by which drowsiness can be detected (and the associated terminology), existing commercial solutions, selected algorithms and research directions, and a collection of examples and case studies. These topics equip the reader to understand this critical field and its applications. Detection Systems and Solutions: Driver Drowsiness is an invaluable resource for researchers and professionals working in intelligent vehicle systems and technologies. Advanced-level students studying computer science and electrical engineering will also find the content helpful.
  table of contents: Introduction -- Driver Drowsiness Detection and Measurement Methods -- Commercial Solutions -- Research Aspects -- Examples.
  note: Aleksandar Čolić, Oge Marques, Borko Furht.
  note: Includes bibliographical references.
  subject:
    topic: Computer vision
  subject:
    topic: Driver assistance systems
  subject:
    topic: Drowsy driving
  subject:
    topic: Computer Imaging, Vision, Pattern Recognition and Graphics
  subject:
    topic: Multimedia Information Systems
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  subject:
    topic: COMPUTERS / General
  classification: TA1634 .C655 2014eb
  classification: 006.3/7
  related item:
    title info:
      title: SpringerBriefs in computer science
  identifier: 9783319115351
  identifier: 3319115359
  identifier: 9783319115344
  identifier: 3319115340 (print)
  identifier: 9783319115344 (print)
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: GW5XE
    record creation date: 141008
    record change date: 20190407115215.0
    record identifier: in00003516458
    language of cataloging:
      language term: eng