ID	原文	译文
52497	为降低光网络决策控制的复杂度，提升光网络的智能化控管能力，文章结合人工智能技术提出了自优化光网络的概念，	In order to reduce the complexity of decision making and improve the intelligent control ability of optical networks, this paper proposes the concept of Self Optimizing Optical Networks (SOON) .
52498	并基于边缘计算与云计算协同的思想，提出了边缘计算与云计算协同的自优化光网络实现机制，	In addition, this paper proposes a SOON implementation mechanism based on edge computing and cloud computing.
52499	通过光传送节点和控制节点的协同机制，为光网络动态提供人工智能所需的计算资源。	The cooperative mechanism among optical transport nodes and control nodes is able to satisfy the computing requirement for artificial intelligence application.
52500	鉴于可见光屏幕通信具有抗干扰能力强、不占用频谱资源和链路部署简单易于交互等特点，	Visible light screen communication has the characteristics of strong anti-interference ability, no occupation of frequency spectrum resources, simple link deployment, and easy interaction.
52501	设计了基于卷积神经网络 (CNN) 的可见光屏幕通信系统。	This paper designs a visible light screen communication system based on Convolutional Neural Network (CNN) .
52502	重点阐述了帧结构的定义、接收单元CNN模块的引入以及解析机制的设计。	It includes the definition of the frame structure, the introduction of the receiving unit CNN module, and the design of the resolution mechanism.
52503	帧结构的定义确保了整个系统的可靠性，丰富了屏幕通信传输内容的多样性;	The definition of the frame structure ensures the reliability of the system and enriches the diversity of the transmission content of the screen communication.
52504	CNN模块的引入使接收单元可以自动识别屏幕发送的内容，	The introduction of the CNN module allows the receiving unit to automatically identify the content sent by the screen.
52505	不依赖传统的定位检测图形，提高了智能化和信息携带量;	It also does not rely on traditional positioning detection patterns, which improves the intelligence and information carrying capacity.
52506	两种解析机制的设计提高了屏幕通信的普适性。	The design of the two resolution mechanisms improves the universality of screen communication.