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Journal article Open Access

Facemask Detector in Surveillance for COVID-19

Sai Vignesh Ramisetty; D Madhumita; K Yashwanth Chowdary


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  <dc:contributor>Blue Eyes Intelligence Engineering &amp; Sciences Publication (BEIESP)</dc:contributor>
  <dc:creator>Sai Vignesh Ramisetty</dc:creator>
  <dc:creator>D Madhumita</dc:creator>
  <dc:creator>K Yashwanth Chowdary</dc:creator>
  <dc:date>2021-07-30</dc:date>
  <dc:description>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. </dc:description>
  <dc:identifier>https://zenodo.org/record/5509804</dc:identifier>
  <dc:identifier>10.35940/ijitee.I9356.0710921</dc:identifier>
  <dc:identifier>oai:zenodo.org:5509804</dc:identifier>
  <dc:language>eng</dc:language>
  <dc:relation>issn:2278-3075</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:source>International Journal of Innovative Technology and Exploring Engineering (IJITEE) 10(9) 64-66</dc:source>
  <dc:subject>This helps us to easily identify the persons wearing masks or not which helps us in taking safety measures according to it.</dc:subject>
  <dc:subject>ISSN</dc:subject>
  <dc:subject>Retrieval Number</dc:subject>
  <dc:title>Facemask Detector in Surveillance for COVID-19</dc:title>
  <dc:type>info:eu-repo/semantics/article</dc:type>
  <dc:type>publication-article</dc:type>
</oai_dc:dc>
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