Abstract:

This paper presents a hybrid deep transfer learning model combined with machine learning methods to effectively detect face masks during the COVID-19 pandemic. The model leverages the power of transfer learning to enhance the accuracy of face mask detection by using pre-trained deep learning networks, fine-tuned for this specific task. By integrating various machine learning techniques, the model is designed to efficiently identify whether individuals are wearing face masks in real-time, contributing to public health safety. This approach aims to address the challenges of accurately detecting face masks in diverse environments, thus providing a reliable tool for monitoring and enforcing mask usage during the ongoing pandemic.

Description:

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