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: Roadside Video Data Analysis
    sub title: Deep Learning
  name:
    name part: Verma, Brijesh.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Zhang, Ligang.
    role:
      role term: author.
  name:
    name part: Stockwell, David.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: si
    date issued: 2017
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XXV, 189 p. 79 illus., 68 illus. in color. online resource.
  abstract: This book highlights the methods and applications for roadside video data analysis, with a particular focus on the use of deep learning to solve roadside video data segmentation and classification problems. It describes system architectures and methodologies that are specifically built upon learning concepts for roadside video data processing, and offers a detailed analysis of the segmentation, feature extraction and classification processes. Lastly, it demonstrates the applications of roadside video data analysis including scene labelling, roadside vegetation classification and vegetation biomass estimation in fire risk assessment.
  table of contents: Chapter 1: Introduction -- Chapter 2: Roadside Video Data Analysis Framework -- Chapter 3: Non-Deep Learning Techniques for Roadside Video Data Analysis -- Chapter 4: Deep Learning Techniques for Roadside Video Data Analysis -- Chapter 5: Case Study: Roadside Video Data Analysis for Fire Risk Assessment -- Chapter 6: Conclusion and Future Insight - References.
  note: by Brijesh Verma, Ligang Zhang, David Stockwell.
  subject:
    topic: Engineering
  subject:
    topic: User interfaces (Computer systems)
  subject:
    topic: Computer graphics
  subject:
    topic: Computational intelligence
  subject:
    topic: Transportation engineering
  subject:
    topic: Traffic engineering
  subject:
    topic: Engineering
  subject:
    topic: Signal, Image and Speech Processing
  subject:
    topic: Computational Intelligence
  subject:
    topic: User Interfaces and Human Computer Interaction
  subject:
    topic: Computer Imaging, Vision, Pattern Recognition and Graphics
  subject:
    topic: Transportation Technology and Traffic Engineering
  classification: TK5102.9
  classification: TA1637-1638
  classification: TK7882.S65
  classification: 621.382
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Studies in Computational Intelligence, 711
  identifier: 9789811045394
  identifier: http://dx.doi.org/10.1007/978-981-10-4539-4
  record info:
    record creation date: 170428
    record change date: 20170428114913.0
    record identifier: 978-981-10-4539-4