Abstract
The papers in this special section focus on machine learning in photonic communication and measurement systems. From being a niche field within computer science, the field of machine learning has gone mainstream within the last couple of years. The reason is that researchers around the world that work within photonics systems and components design have realized that machine learning brings a new set of highly-effective tools that can be used to: 1) design novel components and systems 2) optimize transmission systems and 3) obtain more accurate measurements. Indeed, using machine learning to design the next generation of components and systems as well as measurement systems is an emerging line of research in the photonics community.
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