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Survey towards Masked Face Detection for Pandemic
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 183 - Number 8 |
| Year of Publication: 2021 |
| Authors: Yash Agrawal, Diksha Nitnaware, Gauri Kulkarni, Saurabh Patil, Archana Lomte |
10.5120/ijca2021921370
|
Yash Agrawal, Diksha Nitnaware, Gauri Kulkarni, Saurabh Patil, Archana Lomte . Survey towards Masked Face Detection for Pandemic. International Journal of Computer Applications. 183, 8 ( Jun 2021), 18-21. DOI=10.5120/ijca2021921370
Abstract
Covid19 has given another personality for wearing a veil. It is significant when these covered countenances are recognized precisely and proficiently. As an exceptional face recognition task, face veil identification is substantially more troublesome on account of outrageous impediments which prompt the deficiency of face subtleties. Furthermore, there is basically no current enormous scope precisely marked concealed face dataset, which increments the trouble of face veil discovery. The framework urges to utilize CNN-based profound learning calculations which have done tremendous advancement towards explores in face identification. In this paper, propose a novel CNN-based technique that is shaped by three convolutional neural organizations to recognize the face veil. Plus, in view of the deficiency of face veiled preparing tests, propose another dataset called" face cover dataset" to tweak CNN models. Assess proposed face veil recognition calculation on the face cover testing set, and it accomplishes agreeable execution.
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