July 30, 2021 Journal article Open Access

Sai Vignesh Ramisetty; D Madhumita; K Yashwanth Chowdary

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  <identifier identifierType="URL">https://zenodo.org/record/5509804</identifier>
  <creators>
    <creator>
      <creatorName>Sai Vignesh Ramisetty</creatorName>
      <affiliation>Studying B.Tech (4th year), Department of Electronics and Communication Engineering (Spec in IOT &amp; Sensors), Vellore Institute of Technology, Vellore (Tamil Nadu), India.</affiliation>
    </creator>
    <creator>
      <creatorName>D Madhumita</creatorName>
      <affiliation>Studying B.Tech (4TH year), Department of Electronics and Communication Engineering (Spec in IOT &amp; Sensors), Vellore Institute of Technology, Vellore (Tamil Nadu), India.</affiliation>
    </creator>
    <creator>
      <creatorName>K Yashwanth Chowdary</creatorName>
      <affiliation>Studying B.Tech (4th year), Department of Electronics and Communication Engineering (Spec in IOT &amp; Sensors), Vellore Institute of Technology, Vellore (Tamil Nadu), India.</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Facemask Detector in Surveillance for COVID-19</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2021</publicationYear>
  <subjects>
    <subject>This helps us to easily identify the persons wearing masks or not which helps us in taking safety measures according to it.</subject>
    <subject subjectScheme="issn">2278-3075</subject>
    <subject subjectScheme="handle">100.1/ijitee.I93560710921</subject>
  </subjects>
  <contributors>
    <contributor contributorType="Sponsor">
      <contributorName>Blue Eyes Intelligence Engineering &amp; Sciences Publication (BEIESP)</contributorName>
      <affiliation>Publisher</affiliation>
    </contributor>
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  <dates>
    <date dateType="Issued">2021-07-30</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="JournalArticle"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/5509804</alternateIdentifier>
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    <relatedIdentifier relatedIdentifierType="ISSN" relationType="IsCitedBy" resourceTypeGeneral="JournalArticle">2278-3075</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.35940/ijitee.I9356.0710921</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;Due to this unexpected pandemic we are going on these days, wearing a face mask became mandatory to save ourselves as well as others from the virus. But it is difficult to monitor every citizen whether he is wearing a mask or not. But it is very important. So, to overcome this problem we came up with a solution to monitor every citizen using a deep learning concept. So, we are developing a face mask detector with opencv/keras. This helps us to easily identify the persons wearing masks or not which helps us in taking safety measures according to it. We tried using different types of platforms such as mobilev2net and resnet architecture but the accuracy of resnet architecture is more compared to the other architecture.&amp;nbsp;&lt;/p&gt;</description>
  </descriptions>
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