December 30, 2019 Journal article Open Access

Telugu Maddileti; G. Shriphad Rao; Vaddemani Sai Madhav; Ganti Sharan

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  <identifier identifierType="URL">https://zenodo.org/record/5602630</identifier>
  <creators>
    <creator>
      <creatorName>Telugu Maddileti</creatorName>
      <affiliation>Assistant Professor, ECM Department, Sreenidhi Institute of Science and Technology, Ghatekesar, Telangana-501301.</affiliation>
    </creator>
    <creator>
      <creatorName>G. Shriphad Rao</creatorName>
      <affiliation>ECM Department, Sreenidhi Institute of Science and  Technology, Ghatekesar, Telangana-501301</affiliation>
    </creator>
    <creator>
      <creatorName>Vaddemani Sai Madhav</creatorName>
      <affiliation>ECM Department, Sreenidhi Institute of Science and  Technology, Ghatekesar, Telangana-501301</affiliation>
    </creator>
    <creator>
      <creatorName>Ganti Sharan</creatorName>
      <affiliation>ECM Department, Sreenidhi Institute of Science and  Technology, Ghatekesar, Telangana-501301</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Home Security using Face Recognition  Technology</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2019</publicationYear>
  <subjects>
    <subject>Face recognition, Face-detection, Eigen-faces, Fisher-faces, CNN, neural network, Residual network.</subject>
    <subject subjectScheme="issn">2249-8958</subject>
    <subject subjectScheme="handle">B3917129219/2019©BEIESP</subject>
  </subjects>
  <contributors>
    <contributor contributorType="Sponsor">
      <contributorName>Blue Eyes Intelligence Engineering  &amp; Sciences Publication(BEIESP)</contributorName>
      <affiliation>Publisher</affiliation>
    </contributor>
  </contributors>
  <dates>
    <date dateType="Issued">2019-12-30</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="JournalArticle"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/5602630</alternateIdentifier>
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    <relatedIdentifier relatedIdentifierType="ISSN" relationType="IsCitedBy" resourceTypeGeneral="JournalArticle">2249-8958</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.35940/ijeat.B3917.129219</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;Face is the easiest way to penetrate each other&amp;#39;s personal identity. Face recognition is a method of personal identification using the personal characteristics of an individual to decide the identification of a person. The method of human face recognition consists basically of two levels, namely face detection and face recognition. There are three types of methods that are currently popular in the developed face recognition pattern, those are Eigen faces algorithm, Fisher faces algorithm and CNN neural network for face recognition&lt;/p&gt;</description>
  </descriptions>
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