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: Machine Learning for Audio, Image and Video Analysis
    sub title: Theory and Applications
  name:
    name part: Camastra, Francesco.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Vinciarelli, Alessandro.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxk
    date issued: 2008
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XVI, 494 p. online resource.
  abstract: Machine Learning involves several scientific domains including mathematics, computer science, statistics and biology, and is an approach that enables computers to automatically learn from data. Focusing on complex media and how to convert raw data into useful information, this book offers both introductory and advanced material in the combined fields of machine learning and image/video processing. The machine learning techniques presented enable readers to address many real world problems involving complex data. Examples covering areas such as automatic speech and handwriting transcription, automatic face recognition, and semantic video segmentation are included, along with detailed introductions to algorithms and examples of their applications. The book is organized in four parts: The first focuses on technical aspects, basic mathematical notions and elementary machine learning techniques. The second provides an extensive survey of most relevant machine learning techniques for media processing, while the third part focuses on applications and shows how techniques are applied in actual problems. The fourth part contains detailed appendices that provide notions about the main mathematical instruments used throughout the text. Students and researchers needing a solid foundation or reference, and practitioners interested in discovering more about the state-of-the-art will find this book invaluable. Examples and problems are based on data and software packages publicly available on the web.
  table of contents: From Perception to Computation -- Audio Acquisition, Representation and Storage -- Image and Video Acquisition, Representation and Storage -- Machine Learning -- Machine Learning -- Bayesian Theory of Decision -- Clustering Methods -- Foundations of Statistical Learning and Model Selection -- Supervised Neural Networks and Ensemble Methods -- Kernel Methods -- Markovian Models for Sequential Data -- Feature Extraction Methods and Manifold Learning Methods -- Applications -- Speech and Handwriting Recognition -- Automatic Face Recognition -- Video Segmentation and Keyframe Extraction.
  note: by Francesco Camastra, Alessandro Vinciarelli.
  subject:
    topic: Computer science
  subject:
    topic: Multimedia information systems
  subject:
    topic: Artificial intelligence
  subject:
    topic: Image processing
  subject:
    topic: Pattern recognition
  subject:
    topic: Computer Science
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  subject:
    topic: Pattern Recognition
  subject:
    topic: Image Processing and Computer Vision
  subject:
    topic: Multimedia Information Systems
  classification: Q334-342
  classification: TJ210.2-211.495
  classification: 006.3
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Advanced Information and Knowledge Processing
  identifier: 9781848000070
  identifier: http://dx.doi.org/10.1007/978-1-84800-007-0
  record info:
    record creation date: 100301
    record change date: 20151204185904.0
    record identifier: 978-1-84800-007-0