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:
    non sort: The
    title: Art and Science of Machine Intelligence
    sub title: With An Innovative Application for Alzheimer's Detection from Speech
  name:
    name part: Land Jr., Walker H.
    role:
      role term: creator
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: Schaffer, J. David.
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  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 (XXII, 269 pages 140 illustrations, 72 illustrations in color.)
  abstract: This volume presents several machine intelligence technologies, developed over recent decades, and illustrates how they can be combined in application. One application, the detection of dementia from patterns in speech, is used throughout to illustrate these combinations. This application is a classic stationary pattern detection task, so readers may easily see how these combinations can be applied to other similar tasks. The expositions of the methods are supported by the basic theory they rest upon, and their application is clearly illustrated. The book's goal is to allow readers to select one or more of these methods to quickly apply to their own tasks. Includes a variety of machine intelligent technologies and illustrates how they can work together Shows evolutionary feature subset selection combined with support vector machines and multiple classifiers combined Includes a running case study on intelligent processing relating to Alzheimer's / dementia detection, in addition to several applications of the machine hybrid algorithms .
  table of contents: Introduction -- Background for Genetic Algorithms -- Support Vector Machines (SVMs) -- The Generalized Regression Neural Network (GRNN) Oracle -- Alzheimer's Disease (AD) Background -- Genetic Algorithm (GA)-SVM Paradigm -- GA-SVM Paradigm Applied to Detecting AD from Speech -- Classical Bayesian Networks (BN) MI Developed Bayesian Networks -- Generalization of MI methods -- Selected research studies -- Conclusion.
  note: by Walker H. Land Jr., J. David Schaffer.
  subject:
    topic: Electrical engineering
  subject:
    topic: Biomedical engineering
  subject:
    topic: Pattern recognition
  subject:
    topic: Signal processing
  subject:
    topic: Image processing
  subject:
    topic: Speech processing systems
  subject:
    topic: Computational intelligence
  subject:
    topic: Computational linguistics
  subject:
    topic: Communications Engineering, Networks
  subject:
    topic: Biomedical Engineering and Bioengineering
  subject:
    topic: Pattern Recognition
  subject:
    topic: Signal, Image and Speech Processing
  subject:
    topic: Computational Intelligence
  subject:
    topic: Computational Linguistics
  classification: TK1-9971
  classification: 621.382
  related item:
    title info:
      title: Springer Nature eBook
  identifier: 9783030184964
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record creation date: 190625
    record change date: 20230330184810.4
    record identifier: in00004393602