Abstract
As the Internet of Things (IoT) develops, applying machine learning on optical communications has become a prospective field of research. Scholars have mostly concentrated on algorithmic techniques or specific applications but have been unable to address the distribution of machine-learning technologies and the development of its applications in optical communications from a macro perspective. Therefore, in this paper, machine-learning patents in optical communications are taken as the analytical basis for constructing a patent technology network. The study results revealed that key technologies were primarily in data input and output devices, data-processing methods, wireless communication networks, and the transmission of digital information in optical communications. Such technologies were also applied to perform measurement for diagnostic purposes and medical diagnoses. The technology network model proposed in this paper explores the technological development trends of machine learning in optical communications and serves as a reference for allocating research and development resources.
Funder
Ministry of Science and Technology, Taiwan
Subject
Radiology Nuclear Medicine and imaging,Instrumentation,Atomic and Molecular Physics, and Optics
Cited by
2 articles.
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