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Face Mask Detection by using Optimistic Convolutional Neural Network

Publication Type : Conference Paper

Publisher : 2021 6th International Conference on Inventive Computation Technologies (ICICT)

Source : 2021 6th International Conference on Inventive Computation Technologies (ICICT), IEEE, Coimbatore, India (2021)

Url : https://ieeexplore.ieee.org/document/9358653

Keywords : Convolutional neural networks, Covid-19, Faces, Rail transportation, Real-time systems, Task analysis, Viruses (medical)

Year : 2021

Abstract : COVID-19 pandemic has rapidly increased health crises globally and is affecting our day-to-day lifestyle. A motive for survival recommendations is to wear a safe facemask, stay protected against the transmission of coronavirus. By wearing a facemask, the most effective preventive care must be taken against COVID-19. Monitoring manually if the individuals are wearing facemask correctly and to notify the victim in public and crowded areas is a difficult task. This paper approaches a simplified way to achieve facemask detection and notifying the individual if not wearing facemask. Using Kaggle datasets, the proposed system/model is trained and examined. The system runs in real-time and detects if an individual face has facemask if not then notify the individual personally through text message. The mask is extracted from real-time faces in pub

Cite this Research Publication : K. Suresh, Palangappa, M. B., and Bhuvan, S., “Face Mask Detection by using Optimistic Convolutional Neural Network”, in 2021 6th International Conference on Inventive Computation Technologies (ICICT), Coimbatore, India, 2021.

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