A Review on Performance Enhancement of Deep Learning Based Face Detection System - Rathod, Vinod M.; Agarwal, Sohit; Mohite, Rajendra B.; Chinchawade, Amit Jaykumar; Salunkhe, Madhav Jagannath; Waghmode, Uttam P. (International Journal of Intelligent Systems and Applications in Engineering, 2024)
It is difficult to identify faces since most individuals used masks during the COVID-19 epidemic. The NIST 2020 study states that the current state of the art approaches for facial recognition have an error rate of 20% to 50% when the mask is used. Lately, a plethora of academics have said that they would solve this issue utilizing CNN and other approaches. To positively identify people in certain instances, researchers combined characteristics from the mask-covered and unmasked parts of the face. There is a substantial mistake rate when using these two characteristics or scenarios to identify faces. To get around these problems, you may utilize tools like Principal Component Analysis (PCA).