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Emerging role of machine learning in light-matter interaction

         

摘要

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.

著录项

  • 来源
    《光:科学与应用(英文版)》 |2019年第1期|445-451|共7页
  • 作者单位

    Faculty of Science;

    Institute for Biomedical Materials and Devices;

    University of Technology;

    Sydney;

    NSW 2007;

    Australia;

    Department of Applied Biology and Chemical Technology;

    The Hong Kong Polytechnic University;

    Hong Hum;

    Kowloon;

    Hong Kong SAR;

    China;

    Faculty of Engineering and IT;

    Centre for Artificial Intelligence;

    University of Technology;

    Sydney;

    NSW 2007;

    Australia;

    Swiss Federal Institute of Technology;

    Lausanne(EPFL);

    ISIC;

    Lausanne;

    Switzerland;

  • 原文格式 PDF
  • 正文语种 chi
  • 中图分类 英语;
  • 关键词

    learning; interaction; dealing;

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