A Comprehensive Review of Mask Detection Using Artificial Intelligence: Methods, Challenges, and Applications

PAWAN WHIG

Abstract


Mask detection using artificial intelligence (AI) has gained significant attention in recent times due to the global COVID-19 pandemic and the importance of mask-wearing in curbing the spread of respiratory infections. This review paper presents an in-depth examination of the various AI-based methods and techniques used for mask detection. We explore the diverse approaches, including deep learning, computer vision, and machine learning algorithms, applied to detect masks in images and videos. The paper also discusses the challenges associated with mask detection, such as occlusion, varied mask types, and real-world environmental conditions. Additionally, we delve into the wide-ranging applications of mask detection technology in various sectors, including healthcare, transportation, public spaces, and security. By synthesizing current research and developments in this field, this review paper aims to offer valuable insights into the state-of-the-art mask detection technologies, their limitations, and potential future directions. Understanding the advancements and challenges in mask detection using AI is essential for improving public health and safety measures during pandemics and beyond.

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