Selected article for: "automatically detect and deep learning work"

Author: Ibitoye, O.
Title: A Brief Review of Convolutional Neural Network Techniques for Masked Face Recognition
  • Cord-id: dztn7wnt
  • Document date: 2021_1_1
  • ID: dztn7wnt
    Snippet: Masked face recognition is now an essential part of health safety, security and surveillance systems which offers incredible advantages in our daily lives, especially in the era of the pandemic ushered in by the outbreak of coronavirus disease in the year 2019 (COVID-19). Applications such as;face mask compliance checks, facial security checks, facial attendance records and facial authentication for access control now requires an effective masked face recognition system. The existing systems of
    Document: Masked face recognition is now an essential part of health safety, security and surveillance systems which offers incredible advantages in our daily lives, especially in the era of the pandemic ushered in by the outbreak of coronavirus disease in the year 2019 (COVID-19). Applications such as;face mask compliance checks, facial security checks, facial attendance records and facial authentication for access control now requires an effective masked face recognition system. The existing systems of masked face recognition were developed to automatically detect and understand faces occluded with masks using computer vision and deep learning techniques, the systems are yet to work effectively in real-time. This study gives an analysis of some techniques used for the implementation of masked face recognition system, with emphasis on Convolutional Neural Network (CNN). The strengths and enhancement areas of the highlighted techniques towards real-time implementation were discussed. © 2021 IEEE.

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