Work

AR-TFRA: An AR-Assisted Typical Fault Retrieval and Analysis System for Efficient Power Grid Communication Operation and Maintenance Training

Year: 2024

Type: conference-paper

Source: International Conference on Smart Grid and Energy Engineering (SGEE)

DOI: 10.1109/sgee64306.2024.10865881

Authors: Yuanshan Guo, Lei Wang, Jinglong Zhao, Huiping Meng, Yangyang Wu, Xiaojing Zhao, Zengqiang Yan

Institutions: State Grid Corporation of China (China), Huazhong University of Science and Technology

Language: English

Topic: Augmented Reality Applications

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: closed

OpenAlex ID: W4407404239

FWCI:

Cites: 10

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Related to: 10