A Review on Recognition of Disguise Face Mask Using Novel Deep Convolutional Neural Network
Krishna S Narayanan, P. Nagaraj, Venkatkumar Muneeswaran · 2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) · 2022
Object recognition establishes a connection of different objects present in images or videos. Nowadays, this technology is widely used in transportation management systems, intelligence systems, military equipment acquisition, and also in surgical equipment to obtain a surgical guidance, etc. Wearing a facemask has become a mandate in public places to control the spread of coronavirus. This research study has developed a novel facemask detection model based on a single-shot detector (SSD) to collect real-time images. This process has been implemented in three modules: 1) A network of simple error correction features will be introduced based on SSD and partition in order to achieve a better access speed and satisfy the real-time requirements; 2) Feature Enhancement Module (FEM) is used to strengthen the in-depth features learned by CNN models to improve the visibility of minor substances; 3) A COVID-19-mask will be finally created by considering a large database of face mask images. Test results generate high accuracy while utilizing real-time acquisition and realization of the proposed algorithm.