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Medical face mask detection using modified MobileNetV2
| Content Provider | Scilit |
|---|---|
| Author | Choudhary, Vikrant Singh, Krishna Kant Singh, Akansha |
| Copyright Year | 2021 |
| Description | In this paper, a simple and computationally efficient approach as per the complexity has been presented for Face mask detection using a Deep Learning architecture called MobileNetV2 including some additional specifications for the improvisation of the results. The secondary objective is to keep the pre/post-processing of the images minimal. The presented model is trained on images from the RMFD dataset which includes masked and non-masked people images. The aim is to achieve an accuracy above 95% with a minimum number of parameters after evaluation. Book Name: Recent Trends in Communication and Electronics |
| Related Links | https://api.taylorfrancis.com/content/chapters/edit/download?identifierName=doi&identifierValue=10.1201/9781003193838-45&type=chapterpdf |
| Ending Page | 250 |
| Page Count | 6 |
| Starting Page | 245 |
| DOI | 10.1201/9781003193838-45 |
| Language | English |
| Publisher | Informa UK Limited |
| Publisher Date | 2021-06-19 |
| Access Restriction | Open |
| Subject Keyword | Book Name: Recent Trends in Communication and Electronics Hardware and Architecturee Masked Mobilenetv2 Secondary Architecture Computationally Minimum Improvisation Pre/post |
| Content Type | Text |
| Resource Type | Chapter |
