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  • Nanophotonics and Machine Learning: Concepts, Fundamentals, and Applications

    Nanophotonics and Machine Learning by Yao, Kan; Zheng, Yuebing;

    Concepts, Fundamentals, and Applications

    Series: Springer Series in Optical Sciences; 241;

      • GET 20% OFF

      • The discount is only available for 'Alert of Favourite Topics' newsletter recipients.
      • Publisher's listprice EUR 128.39
      • The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.

        53 249 Ft (50 714 Ft + 5% VAT)
      • Discount 20% (cc. 10 650 Ft off)
      • Discounted price 42 600 Ft (40 571 Ft + 5% VAT)

    53 249 Ft

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    printed on demand

    Why don't you give exact delivery time?

    Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.

    Long description:

    This book, the first of its kind, bridges the gap between the increasingly interlinked fields of nanophotonics and artificial intelligence (AI). While artificial intelligence techniques, machine learning in particular, have revolutionized many different areas of scientific research, nanophotonics holds a special position as it simultaneously benefits from AI-assisted device design whilst providing novel computing platforms for AI. This book is aimed at both researchers in nanophotonics who want to utilize AI techniques and researchers in the computing community in search of new photonics-based hardware. The book guides the reader through the general concepts and specific topics of relevance from both nanophotonics and AI, including optical antennas, metamaterials, metasurfaces, and other photonic devices on the one hand, and different machine learning paradigms and deep learning algorithms on the other. It goes on to comprehensively survey inverse techniques for device design, AI-enabled applications in nanophotonics, and nanophotonic platforms for AI. This book will be essential reading for graduate students, academic researchers, and industry professionals from either side of this fast-developing, interdisciplinary field.

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    Table of Contents:

    Chapter1. Fundamentals of nanophotonics.- Chapter2. Nanophotonic devices and platforms. - Chapter3. Fundamentals of machine learning.- Chapter4. DL-assisted inverse design in nanophotonics.- Chapter5. DL-enabled applications in nanophotonics.- Chapter6. Nanophotonic and optical platforms for DL.

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