A Deep Learning Approach for Efficient Anomaly Detection in WSNs.

Saved in:
Bibliographic Details
Title: A Deep Learning Approach for Efficient Anomaly Detection in WSNs.
Authors: S., Arul Jothi1, saj.cse@psgtech.ac.in, R., Venkatesan2, rve.cse@psgtech.ac.in
Source: International Journal of Computers, Communications & Control; Feb2023, Vol. 18 Issue 1, p1-21, 21p
Database: Applied Science & Technology Source
FullText Links:
  – Type: pdflink
Text:
  Availability: 0
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 161914174
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: A Deep Learning Approach for Efficient Anomaly Detection in WSNs.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22S%2E%2C+Arul+Jothi%22">S., Arul Jothi</searchLink><relatesTo>1</relatesTo>, <i>saj.cse@psgtech.ac.in</i><br /><searchLink fieldCode="AU" term="%22R%2E%2C+Venkatesan%22">R., Venkatesan</searchLink><relatesTo>2</relatesTo>, <i>rve.cse@psgtech.ac.in</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Computers%2C+Communications+%26+Control%22">International Journal of Computers, Communications & Control</searchLink>; Feb2023, Vol. 18 Issue 1, p1-21, 21p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=161914174
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.15837/ijccc.2023.1.4756
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 21
        StartPage: 1
    Titles:
      – TitleFull: A Deep Learning Approach for Efficient Anomaly Detection in WSNs.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: S., Arul Jothi
      – PersonEntity:
          Name:
            NameFull: R., Venkatesan
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 02
              Text: Feb2023
              Type: published
              Y: 2023
          Identifiers:
            – Type: issn-print
              Value: 18419836
          Numbering:
            – Type: volume
              Value: 18
            – Type: issue
              Value: 1
          Titles:
            – TitleFull: International Journal of Computers, Communications & Control
              Type: main
ResultId 1