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Face mask recognition system using CNN model.
Kaur, Gagandeep; Sinha, Ritesh; Tiwari, Puneet Kumar; Yadav, Srijan Kumar; Pandey, Prabhash; Raj, Rohit; Vashisth, Anshu; Rakhra, Manik.
  • Kaur G; Department of Computer Science and Engineering, Lovely Professional university Phagwara, Punjab 144411, India.
  • Sinha R; Department of Computer Science and Engineering, Lovely Professional university Phagwara, Punjab 144411, India.
  • Tiwari PK; Department of Computer Science and Engineering, Lovely Professional university Phagwara, Punjab 144411, India.
  • Yadav SK; Department of Computer Science and Engineering, Lovely Professional university Phagwara, Punjab 144411, India.
  • Pandey P; Department of Computer Science and Engineering, Lovely Professional university Phagwara, Punjab 144411, India.
  • Raj R; Department of Computer Science and Engineering, Lovely Professional university Phagwara, Punjab 144411, India.
  • Vashisth A; Department of Computer Science and Engineering, Lovely Professional university Phagwara, Punjab 144411, India.
  • Rakhra M; Department of Computer Science and Engineering, Lovely Professional university Phagwara, Punjab 144411, India.
Neurosci Inform ; 2(3): 100035, 2022 Sep.
Article in English | MEDLINE | ID: covidwho-2265773
ABSTRACT
COVID-19 epidemic has swiftly disrupted our day-to-day lives affecting the international trade and movements. Wearing a face mask to protect one's face has become the new normal. In the near future, many public service providers will expect the clients to wear masks appropriately to partake of their services. Therefore, face mask detection has become a critical duty to aid worldwide civilization. This paper provides a simple way to achieve this objective utilising some fundamental Machine Learning tools as TensorFlow, Keras, OpenCV and Scikit-Learn. The suggested technique successfully recognises the face in the image or video and then determines whether or not it has a mask on it. As a surveillance job performer, it can also recognise a face together with a mask in motion as well as in a video. The technique attains excellent accuracy. We investigate optimal parameter values for the Convolutional Neural Network model (CNN) in order to identify the existence of masks accurately without generating over-fitting.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Clinical_trials Language: English Journal: Neurosci Inform Year: 2022 Document Type: Article Affiliation country: J.neuri.2021.100035

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Clinical_trials Language: English Journal: Neurosci Inform Year: 2022 Document Type: Article Affiliation country: J.neuri.2021.100035