KEYWORDS: Thermography, RGB color model, Roads, Temperature metrology, Neural networks, Detection and tracking algorithms, Machine learning, Digital cameras, Object recognition
A thermal image taken by a thermal camera and an RGB color picture were arranged in a dataset pair; the datasets were learned using a deep learning algorithm called pix2pix. After the sufficient training in the machine learning, it was possible to generate a thermal image from a color image taken with a digital camera. This paper provides a new method of generating thermal image without a thermal camera; the thermal camera is required when we create training materials. Furthermore, a method for detecting abnormal temperatures using deep learning is proposed. Features of thermal images are concerned and evaluated the results of our method.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.