A Face Mask Detection Model Based on Improved Genetic Algorithm- Optimized Convolution Neural Network in COVID-19 Pandemic

Wearing masks is an essential means of ensuring public safety under the pandemic of COVID-19. Detecting whether people wear masks correctly is vital for preventing and controlling new crown epidemics. In response to the poor effectiveness of current basic deep learning methods for mask-wearing detection, this paper proposes a convolutional neural network optimized by an improved genetic algorithm to detect face masks. We used an improved genetic algorithm to optimize the parameters in the convolutional neural network and then compared the results with those of other papers. The results show that the proposed method is more effective in detecting the wearing of masks with a correct rate of up to 99.125% and can provide practical help and guidance for the prevention and control of the COVID-19 epidemic.