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CoViMask: A Novel Face Mask Type Detector Using Convolutional Neural Networks

Publication Type : Book Chapter

Publisher : IEEE

Source : International Conference on Wireless Communications Signal Processing and Networking (WiSPNET)

Url : https://ieeexplore.ieee.org/abstract/document/9767107

Campus : Amritapuri

School : School of Computing

Year : 2022

Abstract : The COVID-19 pandemic has led to many lifestyle changes, one of them being the mandatory use of face masks in public settings. Given the importance of masks, there are various types for people to use, such as cloth and N95. A proper mask must be used to protect oneself and others from the spread of the coronavirus. This paper proposes CoViMask, a face mask type detector that detects the type of mask that a person is wearing, and is trained using a custom-made dataset. Accuracy, precision and recall are used to evaluate the proposed method. The paper also mentions the application areas. The results obtained prove that CoViMask is efficient in mask type detection and may aid in controlling the spread of covid.

Cite this Research Publication : Rangasrinivasan, Sahana, Sri Lohitha Bhagam, Nair K. Athira, Kondapi Niharika, Anjuna D. Raj, and T. Anjali. "Covimask: A novel face mask type detector using convolutional neural networks." In 2022 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET), pp. 24-27. IEEE, 2022.

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