Journal article Open Access
Sai Vignesh Ramisetty; D Madhumita; K Yashwanth Chowdary
{ "DOI": "10.35940/ijitee.I9356.0710921", "container_title": "International Journal of Innovative Technology and Exploring Engineering (IJITEE)", "language": "eng", "title": "Facemask Detector in Surveillance for COVID-19", "issued": { "date-parts": [ [ 2021, 7, 30 ] ] }, "abstract": "<p>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. </p>", "author": [ { "family": "Sai Vignesh Ramisetty" }, { "family": "D Madhumita" }, { "family": "K Yashwanth Chowdary" } ], "page": "64-66", "volume": "10", "type": "article-journal", "issue": "9", "id": "5509804" }
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