Generative Adversarial Networks based image generation of insulator
Zhijun Liu, Haifeng Qiu, Liguo Weng, Man Luo, Xiaowei Zhu, Yanghui Zhang · 2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC) · 2022
In recent years, the combination of artificial intelligence and power systems has been increasing. However, the collection of image datasets of power equipment is limited by places and environments, so the number of collected datasets is relatively small, which makes it unable to provide sufficient data support for specific applications. We propose to use Generative Adversarial Networks to generate images of electrical equipment from existing sparse datasets, thereby increasing the size of the electrical equipment dataset. In this paper, three generative adversarial networks with different structures are used to generate images of insulator and to assess the caliber of images produced by the three models, the analysis of loss function image and FID score of generated images is performed.