View in EDS PDF Full Text ePub Full Text

Deep Learning Applications for Cyber-Physical Systems

Saved in:
Bibliographic Details
Title: Deep Learning Applications for Cyber-Physical Systems
Description: Big data generates around us constantly from daily business, custom use, engineering, and science activities. Sensory data is collected from the internet of things (IoT) and cyber-physical systems (CPS). Merely storing such a massive amount of data is meaningless, as the key point is to identify, locate, and extract valuable knowledge from big data to forecast and support services. Such extracted valuable knowledge is usually referred to as smart data. It is vital to providing suitable decisions in business, science, and engineering applications. Deep Learning Applications for Cyber-Physical Systems provides researchers a platform to present state-of-the-art innovations, research, and designs while implementing methodological and algorithmic solutions to data processing problems and designing and analyzing evolving trends in health informatics and computer-aided diagnosis in deep learning techniques in context with cyber physical systems. Covering topics such as smart medical systems, intrusion detection systems, and predictive analytics, this text is essential for computer scientists, engineers, practitioners, researchers, students, and academicians, especially those interested in the areas of internet of things, machine learning, deep learning, and cyber-physical systems.
Authors: Monica R. Mundada, S. Seema, Srinivasa K.G, M. Shilpa
Resource Type: eBook.
Subjects: Medical technology, Systems engineering, Machine learning--Industrial applications, Cooperating objects (Computer systems)--Industrial applications
Categories: COMPUTERS / Programming / Algorithms, COMPUTERS / Artificial Intelligence / General, COMPUTERS / Computer Engineering
Database: eBook Collection (EBSCOhost)
FullText Links:
  – Type: ebook-pdf
  – Type: ebook-epub
Text:
  Availability: 0
Header DbId: nlebk
DbLabel: eBook Collection (EBSCOhost)
An: 3102732
RelevancyScore: 1110
AccessLevel: 6
PubType: eBook
PubTypeId: ebook
PreciseRelevancyScore: 1109.74133300781
IllustrationInfo
ImageInfo – Size: thumb
  Target: https://rps2images.ebscohost.com/rpsweb/othumb?id=NL$3102732$PDF&s=r
– Size: medium
  Target: https://rps2images.ebscohost.com/rpsweb/othumb?id=NL$3102732$PDF&s=d
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Deep Learning Applications for Cyber-Physical Systems
– Name: Abstract
  Label: Description
  Group: Ab
  Data: Big data generates around us constantly from daily business, custom use, engineering, and science activities. Sensory data is collected from the internet of things (IoT) and cyber-physical systems (CPS). Merely storing such a massive amount of data is meaningless, as the key point is to identify, locate, and extract valuable knowledge from big data to forecast and support services. Such extracted valuable knowledge is usually referred to as smart data. It is vital to providing suitable decisions in business, science, and engineering applications. Deep Learning Applications for Cyber-Physical Systems provides researchers a platform to present state-of-the-art innovations, research, and designs while implementing methodological and algorithmic solutions to data processing problems and designing and analyzing evolving trends in health informatics and computer-aided diagnosis in deep learning techniques in context with cyber physical systems. Covering topics such as smart medical systems, intrusion detection systems, and predictive analytics, this text is essential for computer scientists, engineers, practitioners, researchers, students, and academicians, especially those interested in the areas of internet of things, machine learning, deep learning, and cyber-physical systems.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Monica+R%2E+Mundada%22">Monica R. Mundada</searchLink><br /><searchLink fieldCode="AR" term="%22S%2E+Seema%22">S. Seema</searchLink><br /><searchLink fieldCode="AR" term="%22Srinivasa+K%2EG%22">Srinivasa K.G</searchLink><br /><searchLink fieldCode="AR" term="%22M%2E+Shilpa%22">M. Shilpa</searchLink>
– Name: TypePub
  Label: Resource Type
  Group: TypPub
  Data: eBook.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Medical+technology%22">Medical technology</searchLink><br /><searchLink fieldCode="DE" term="%22Systems+engineering%22">Systems engineering</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+learning--Industrial+applications%22">Machine learning--Industrial applications</searchLink><br /><searchLink fieldCode="DE" term="%22Cooperating+objects+%28Computer+systems%29--Industrial+applications%22">Cooperating objects (Computer systems)--Industrial applications</searchLink>
– Name: SubjectBISAC
  Label: Categories
  Group: Su
  Data: <searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+Programming+%2F+Algorithms%22">COMPUTERS / Programming / Algorithms</searchLink><br /><searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+Artificial+Intelligence+%2F+General%22">COMPUTERS / Artificial Intelligence / General</searchLink><br /><searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+Computer+Engineering%22">COMPUTERS / Computer Engineering</searchLink>
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=nlebk&AN=3102732
RecordInfo BibRecord:
  BibEntity:
    Classifications:
      – Code: 006.331
        Scheme: ddc
        Type: prePub
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Medical technology
        Type: general
      – SubjectFull: Systems engineering
        Type: general
      – SubjectFull: Machine learning--Industrial applications
        Type: general
      – SubjectFull: Cooperating objects (Computer systems)--Industrial applications
        Type: general
    Titles:
      – TitleFull: Deep Learning Applications for Cyber-Physical Systems
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Monica R. Mundada
      – PersonEntity:
          Name:
            NameFull: S. Seema
      – PersonEntity:
          Name:
            NameFull: Srinivasa K.G
      – PersonEntity:
          Name:
            NameFull: M. Shilpa
      – PersonEntity:
          Name:
            NameFull: Monica R. Mundada
      – PersonEntity:
          Name:
            NameFull: S. Seema
      – PersonEntity:
          Name:
            NameFull: Srinivasa K.G
      – PersonEntity:
          Name:
            NameFull: M. Shilpa
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2022
            – D: 22
              M: 11
              Type: profile
              Y: 2021
          Identifiers:
            – Type: isbn-print
              Value: 9781799881612
            – Type: isbn-electronic
              Value: 9781799881636
            – Type: isbn-electronic
              Value: 9781799881643
          Titles:
            – TitleFull: Deep Learning Applications for Cyber-Physical Systems
              Type: main
ResultId 1