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Emerging role of machine learning in light-matter interaction
Machine learning has provided a huge wave of innovation in multiple fields, including computer vision, medical diagnosis, life sciences, molecular design, and instrumental development. This perspective focuses on the implementation of machine learning in dealing with light-matter interaction, which...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6804848/ https://www.ncbi.nlm.nih.gov/pubmed/31645928 http://dx.doi.org/10.1038/s41377-019-0192-4 |
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author | Zhou, Jiajia Huang, Bolong Yan, Zheng Bünzli, Jean-Claude G. |
author_facet | Zhou, Jiajia Huang, Bolong Yan, Zheng Bünzli, Jean-Claude G. |
author_sort | Zhou, Jiajia |
collection | PubMed |
description | Machine learning has provided a huge wave of innovation in multiple fields, including computer vision, medical diagnosis, life sciences, molecular design, and instrumental development. This perspective focuses on the implementation of machine learning in dealing with light-matter interaction, which governs those fields involving materials discovery, optical characterizations, and photonics technologies. We highlight the role of machine learning in accelerating technology development and boosting scientific innovation in the aforementioned aspects. We provide future directions for advanced computing techniques via multidisciplinary efforts that can help to transform optical materials into imaging probes, information carriers and photonics devices. |
format | Online Article Text |
id | pubmed-6804848 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-68048482019-10-23 Emerging role of machine learning in light-matter interaction Zhou, Jiajia Huang, Bolong Yan, Zheng Bünzli, Jean-Claude G. Light Sci Appl Perspective Machine learning has provided a huge wave of innovation in multiple fields, including computer vision, medical diagnosis, life sciences, molecular design, and instrumental development. This perspective focuses on the implementation of machine learning in dealing with light-matter interaction, which governs those fields involving materials discovery, optical characterizations, and photonics technologies. We highlight the role of machine learning in accelerating technology development and boosting scientific innovation in the aforementioned aspects. We provide future directions for advanced computing techniques via multidisciplinary efforts that can help to transform optical materials into imaging probes, information carriers and photonics devices. Nature Publishing Group UK 2019-09-11 /pmc/articles/PMC6804848/ /pubmed/31645928 http://dx.doi.org/10.1038/s41377-019-0192-4 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Perspective Zhou, Jiajia Huang, Bolong Yan, Zheng Bünzli, Jean-Claude G. Emerging role of machine learning in light-matter interaction |
title | Emerging role of machine learning in light-matter interaction |
title_full | Emerging role of machine learning in light-matter interaction |
title_fullStr | Emerging role of machine learning in light-matter interaction |
title_full_unstemmed | Emerging role of machine learning in light-matter interaction |
title_short | Emerging role of machine learning in light-matter interaction |
title_sort | emerging role of machine learning in light-matter interaction |
topic | Perspective |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6804848/ https://www.ncbi.nlm.nih.gov/pubmed/31645928 http://dx.doi.org/10.1038/s41377-019-0192-4 |
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