高电压技术2024，Vol.50Issue(5)：1813-1825,13.DOI:10.13336/j.1003-6520.hve.20232149
大模型时代:电力视觉技术新起点
The Era of Large Models:A New Starting Point for Electric Power Vision Technology
摘要
Abstract
With the widespread applications of drones,inspection robots,and remote monitoring systems in power sce-narios such as transmission,transformation,distribution,and safety supervision,the power vision technology is utilized to automatically process massive inspection images,thus the intelligent operation and maintenance level of power systems can be further enhanced,playing a crucial role in the rapid advancement of China's source-grid-load-storage integration process.With the rise of general-purpose large vision models,the electric power vision technology is embarking on an important transition from the traditional deep learning era to the era of large models.In this paper,the latest research pro-gress in electric power vision technology and general-purpose large vision models is summarized.Combined the precedents of large vision models'applications in various public scenarios,three main capability boundary issues that large vision models will face in the field of power vision are investigated.From initially attempting to apply gen-eral-purpose large vision models to establishing power-specific large vision models,the four model application paradigms to break through the capability boundaries of large vision models are proposed.Finally,the impact of large vision models on electric power vision researchers is analyzed,and prospects in the development direction of electric power vision technology under the wave of large models are put forward.关键词
电力视觉/视觉大模型/目标检测/图像分割/深度学习/图像处理Key words
electric power vision/large vision models/object detection/image segmentation/deep learning/image pro-cessing引用本文复制引用
赵振兵,冯烁,席悦,张靖梁,翟永杰,赵文清..大模型时代:电力视觉技术新起点[J].高电压技术,2024,50(5):1813-1825,13.基金项目
国家自然科学基金(U21A20486 （）
62373151 （）
62371118 （）
62303184) （）
河北省自然科学基金(F2021502008 （）
F2021502013) （）
中央高校基本科研业务费专项资金(2023JC006).Project supported by National Natural Science Foundation of China(U21A20486,62373151,62371118,62303184),Natural Science Foundation of Hebei Province(F2021502008,F2021502013),Fundamental Research Funds for the Central Universities(2023JC006). （2023JC006）
