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Nanophotonics and machine learning =...

Yao, Kan.

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Nanophotonics and machine learning = concepts, fundamentals, and applications /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Nanophotonics and machine learning/ by Kan Yao, Yuebing Zheng.
其他題名:	concepts, fundamentals, and applications /
作者:	Yao, Kan.
其他作者:	Zheng, Yuebing.
出版者:	Cham :Springer International Publishing : : 2023.,
面頁冊數:	xii, 178 p. :ill., digital ;24 cm.
內容註:	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.
Contained By:	Springer Nature eBook
標題:	Nanophotonics. -
電子資源:	https://doi.org/10.1007/978-3-031-20473-9
ISBN:	9783031204739

Nanophotonics and machine learning = concepts, fundamentals, and applications /
Yao, Kan.

Nanophotonics and machine learningconcepts, fundamentals, and applications /[electronic resource] :by Kan Yao, Yuebing Zheng. - Cham :Springer International Publishing :2023. - xii, 178 p. :ill., digital ;24 cm. - Springer series in optical sciences,v. 2411556-1534 ;. - Springer series in optical sciences ;v. 241..

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.

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.

ISBN: 9783031204739

Standard No.: 10.1007/978-3-031-20473-9doiSubjects--Topical Terms:

1085314
Nanophotonics.

LC Class. No.: TA1530

Dewey Class. No.: 621.365

Nanophotonics and machine learning = concepts, fundamentals, and applications /
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520 $a 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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