A global outbreak of COVID-19 has been spreading rapidly since 2019. This pandemic is making human existence more complex and intricate and thousands have been killed by this disease. A lack of antiviral medications is one reason for the proliferation of the COVID-19 virus. People wear masks while going outside due to the spread of Corona virus. Consequently, the system cannot identify their faces while wearing the masks. Introduce a system that can identify celebrities' masked faces after being trained with 100 random images from an online source to overcome this issue. In this paper, the input images are pre-processed to improve the quality and clarity of the image. A real time masked face recognition system is proposed for face mask detection using YOLOV4. The pre-processed equalized images are fed into the YOLOV4 model for the detection of masked face image. Finally, the tested and trained images are detected the masked face image of random celebrities with high accuracy of detection than other state-of-the-art methods. The proposed method yields the accuracy rate of 98.04%. This computerized masked face recognition system has proven particularly useful in the current crisis.