Thermal Imaging in the Age of AI

Artificial intelligence and machine learning increasingly enhance imaging workflows across both the visible and thermal spectrum. While the analytical methods are largely shared, infrared thermography adds the crucial dimension of radiometric temperature measurement, enabling quantitative assessment of thermal behavior rather than purely visual interpretation. This session introduces how data-driven techniques can strengthen thermographic inspection, monitoring, and automation, highlighting the added value of temperature-resolved information.

This content is designed for both newcomers to infrared imaging and experienced professionals interested in integrating AI-assisted thermal analysis into industrial, engineering, and research applications.

If you're new to thermography or would like a deeper understanding of its principles and advantages, explore these resources:

• Thermography Fundamentals Video Series
• Photonics Webinar: Introduction to Thermography

About the presenter
Stephan Larmann earned a Master of Science degree in physics from the University of Göttingen in 1987, complemented by a specialized crash course in marketing technical innovations. His early experimental work involved using lasers to stimulate chemical reactions and employing infrared spectral analysis to measure yields based on varying parameters. Larmann has since built a career spanning decades, accumulating extensive experience in analytical instrumentation and vision applications across a wide range of industries.