Wilson A N, Khushi Gupta, Balu Harshavardan Koduru, Abhinav Kumar, Ajit Jha, and Linga Reddy Cenkeramaddi, “Recent Advances in Thermal Imaging and It’s Applications using Machine Learning: A Review,” has been accepted for publication in the IEEE Sensors Journal (2023).
Keywords: Imaging, Cameras, Sensors, Temperature sensors, Optical sensors, Machine learning, Thermal sensing, cameras, data privacy, image colour analysis, image sensors, infrared imaging, learning (artificial intelligence), reviews, machine-learning techniques, RGB imaging, thermal cameras, thermal images, thermal imaging sensor technology, thermal imaging technology, thermal imaging-based applications
Abstract: Recent advancements in thermal imaging sensor technology have resulted in the use of thermal cameras in a variety of applications, including automotive, industrial, medical, defense and space, agriculture, and other related fields. Thermal imaging, unlike RGB imaging, does not rely on background light, and the technique is nonintrusive while also protecting privacy. This review article focuses on the most recent advancements in thermal imaging technology, key performance parameters, an overview of its applications, and machine-learning techniques applied to thermal images for various tasks. This article begins with the most recent advancements in thermal imaging, followed by a classification of thermal cameras and their key specifications, and finally a review of machine-learning techniques used on thermal images for various applications. This detailed review article is highly useful for designing thermal imaging-based applications using various machine-learning techniques.
More details: DOI: 10.1109/JSEN.2023.3234335