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dc.contributor.authorBhaik, Anubha
dc.contributor.authorSingh, Vaishnavi
dc.contributor.authorGandotra, Ekta
dc.contributor.authorGupta, Deepak
dc.date2022-12
dc.date.accessioned2022-12-14T13:18:35Z
dc.date.available2022-12-14T13:18:35Z
dc.identifier.issn1989-1660
dc.identifier.urihttps://reunir.unir.net/handle/123456789/13929
dc.description.abstractCoronavirus disease 2019 has had a pressing impact on people all around the world. Ceasing the spread of this infectious disease is the urgent need of the hour. A vital method of protection against the virus is wearing masks in public areas. Not merely wearing masks but wearing masks properly can ensure that the respiratory droplets do not get transmitted to other people. In this paper, we have proposed a deep learning-based model, which can be used to detect people who are not wearing their face masks properly. A convolutional neural network model based on the concept of transfer learning is trained on a self-made dataset of images and implemented with light-weighted neural network called MobileNetV2 for mobile architectures. OpenCV is used with Caffe framework to detect faces in an input frame which are further forwarded to our trained convolutional neural network for classification. The method has been implemented on various input images and classification results have been obtained for the same. The experimental results show that the proposed model achieves a testing accuracy and training accuracy of 93.58% and 92.27% respectively. Optimal results with high confidence scores and correct classification have also been achieved when the proposed model was tested on individual input images.es_ES
dc.language.isoenges_ES
dc.publisherInternational Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI)es_ES
dc.relation.ispartofseries;vol. 7, nº 7
dc.relation.urihttps://ijimai.org/journal/bibcite/reference/3016es_ES
dc.rightsopenAccesses_ES
dc.subjectcoronavirus COVID-19es_ES
dc.subjectmask classificationes_ES
dc.subjectmobileNetV2es_ES
dc.subjectopenCVes_ES
dc.subjecttransfer learninges_ES
dc.subjectIJIMAIes_ES
dc.titleDetection of Improperly Worn Face Masks using Deep Learning – A Preventive Measure Against the Spread of COVID-19es_ES
dc.typearticlees_ES
reunir.tag~IJIMAIes_ES
dc.identifier.doihttps://doi.org/10.9781/ijimai.2021.09.003


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