Face Mask Detection Classifier and Model Pruning with Keras-Surgeon
Alok Negi, Prachi Chauhan, Krishan Kumar, Ravindra Kumar Singh Rajput
Abstract
Multidisciplinary initiatives in the new world of coronavirus were combined to limit the spread of the pandemic. Interestingly, the AI group was a part of those efforts. This result-based approach is used to help scan, assess, predict and track current patients and possibly potential patients. Developments for tracking social distances or recognizing face masks have made headlines in particular. Most current advanced approaches to face mask recognition are built based on deep learning which is dependent on a large number of face samples. Nearly everybody wears a mask during corona virus outbreak in order to effectively avoid the spread of COVID-19 virus. Our goal is to train a customized deep learning model that helps to detect even if or not a person wears a mask and study the concept of model pruning with Keras-Surgeon. Model pruning can be efficient in reducing model size, so that it can be easily implemented and inferred on embedded systems.