With the development of smart grids, drones have been widely used for inspecting power transmission lines, generating a large amount of insulator image data. Relying on manual inspection for this task results in a huge workload and the risk of missed detections due to human fatigue. Here, we ...
Firstly, we design a novel weather domain synthesis (WDSt) module to convert various weather-conditioned insulator images to the uniform weather domain to decrease the existing domain gap. To further improve the detection performance, we leverage the attention mechanism to construct the Cros...
Deep architecture for high-speed railway insulator surface defect detection: Denoising autoencoder with multitask learning. IEEE Trans. Instrum. Meas. 2018, 68, 2679–2690. [Google Scholar] [CrossRef] Yu, H.; Li, Q.; Tan, Y.; Gan, J.; Wang, J.; Geng, Y.A.; Jia, L. A coarse-...
proposed a latent-space pointwise ensemble method to improve the structure of a GAN to generate normal samples for the detection of overhead insulator defects [9] . However, CNN inherently has a strong generalization ability and local perception, which makes the model generate sample spaces with ...
Significant improvements in insulator detection performance have been achieved using the method proposed in this paper. It can not only effectively improve the detection accuracy, but also make the missed detection rate lower to meet the requirements of insulator defect detection and fault warning ...
To overcome challenges such as intricate insulator backgrounds, small defect scales, and notable differences in target scales that reduce detection accuracy, we propose the AC-YOLO insulator multi-defect detection network based on adaptive attention fusion. To elaborate, we introduce an ada...
Intelligent Identification Method of Hydrophobic Grade of Composite Insulator Based on Efficient GA-YOLO Former Network object detectionswin transformerGAM attention mechanismBiFPNSILICONE-RUBBERThe hydrophobia of composite insulators is a parameter closely related to insulation ... Z Song,X Huang,C Ji,.....
Due to the small size of the insulator defect, the detection accuracy is very sensitive to the spatial information of the feature map. Referring to the structure of CBAM [31], this paper improves the scSE into a serial structure so that the feature map is first processed by the channel ...
This approach significantly boosts detection precision, diminishes false positive rates, and fulfills real-time insulator localization requirements in power system inspections. Keywords: deep learning; image processing; insulator; defect detection; YOLOv5...
Han, G.; Zhang, M.; Wu, W.; He, M.; Liu, K.; Qin, L.; Liu, X. Improved U-Net based insulator image segmentation method based on attention mechanism.Energy Rep.2021,7, 210–217. [Google Scholar] [CrossRef] Wang, H.; Miao, F. Building extraction from remote sensing images us...