Scholarlink

The expeditious advancement of artificial intelligence (AI) facilitates a wide range of applications across different domains; however, it also introduces substantial challenges concerning speed and energy consumption, driven by the explosive growth of data. Spanning the breadth of research and real implementation, the rise of artificial intelligence (AI) and machine learning (ML) has fundamentally altered traditional critical thinking methodologies. This paper investigates the essential parts of artificial intelligence (AI) and machine learning (ML), emphasizing their crucial role in advancing the capabilities of optics and photonics technologies. Starting with basic definitions and frameworks, discuss different AI/ML algorithms used in optics.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Machine Learning for Optical Network: A Survey

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Saumya Srivastava,
  • Anuja Singh,
  • Pradeep Kumar Verma,
  • Lalit Kumar,
  • Pankaj Vishwakarma,
  • Diksha Pandey

摘要

The expeditious advancement of artificial intelligence (AI) facilitates a wide range of applications across different domains; however, it also introduces substantial challenges concerning speed and energy consumption, driven by the explosive growth of data. Spanning the breadth of research and real implementation, the rise of artificial intelligence (AI) and machine learning (ML) has fundamentally altered traditional critical thinking methodologies. This paper investigates the essential parts of artificial intelligence (AI) and machine learning (ML), emphasizing their crucial role in advancing the capabilities of optics and photonics technologies. Starting with basic definitions and frameworks, discuss different AI/ML algorithms used in optics.