Exploring key machine learning technologies and developments in photonics from the perspective of patent examiners Online publication date: Mon, 30-Dec-2024
by Shu-Hao Chang; Chin-Yuan Fan
International Journal of Technology, Policy and Management (IJTPM), Vol. 24, No. 4, 2024
Abstract: As smart applications mature, the application of machine learning technologies in photonics has become a prospective research area. Thus, the present study investigated various patents identified and cited by examiners, and a technology network model was employed to identify key technologies. Several major technologies were identified, namely those pertaining to electric digital data processing, graphical data reading, signalling and calling systems, vehicles, vehicle fittings, and vehicle parts. Various differences between the technologies cited by applicants and examiners were discovered. The technologies most frequently cited by applicants pertained to diagnoses, surgeries, and identification, whereas those most often cited by examiners pertained to electric digital data processing; notably, examiners used the technologies in this field to approve, reject, or limit the scope of patent rights. The results of the present study can serve as a reference for researching and improving resource allocation.
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