首页|Data augmentation method for insulators based on Cycle-GAN
Data augmentation method for insulators based on Cycle-GAN
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
国家科技期刊平台
NETL
NSTL
万方数据
Data augmentation method for insulators based on Cycle-GAN
Data augmentation is an important task of using existing data to expand data sets.Using generative countermeasure network technology to realize data augmentation has the advantages of high-quality generated samples,simple training,and fewer restrictions on the number of generated samples.However,in the field of transmission line insulator images,the freely synthesized samples are prone to produce fuzzy backgrounds and disordered samples of the main insulator features.To solve the above problems,this paper uses the cycle generative adversarial network(Cycle-GAN)used for domain conversion in the generation countermeasure network as the initial framework and uses the self-attention mechanism and channel attention mechanism to assist the conversion to realize the mutual conversion of different insulator samples.The attention module with prior knowledge is used to build the generation countermeasure network,and the generative adversarial network(GAN)model with local controllable generation is built to realize the directional generation of insulator belt defect samples.The experimental results show that the samples obtained by this method are improved in a number of quality indicators,and the quality effect of the samples obtained is excellent,which has a reference value for the data expansion of insulator images.
Data expansionDeep learningGenerate confrontation networkInsulator
Run Ye、Azzedine Boukerche、Xiao-Song Yu、Cheng Zhang、Bin Yan、Xiao-Jia Zhou
展开 >
School of Automation Engineering,University of Electronic Science and Technology of China,Chengdu,611731,China
Yangtze River Delta Research Institute(Huzhou),University of Electronic Science and Technology of China,Huzhou,313001,China
School of Electrical Engineering and Computer Science,University of Ottawa,Ottawa,K1N6N5,Canada
Data expansion Deep learning Generate confrontation network Insulator
国家科技期刊平台
NSTL
万方数据
