Transmission Lines Scenes Classification Based on Optimized VGG-16

Insulators are important part of transmission lines. Traditionally, insulator-detection methods mainly relied on manual operation, which suffered from low efficiency and poor safety. Due to the rapid development of deep learning, convolutional neural networks(CNNs) have been widely applied in the field of image classification. However, traditional CNNs have poor performance in transmission lines scenes classification. We propose an optimized deep new network based on traditional CNNs. The experimental results show that the proposed optimization method can improve the accuracy of transmission lines scenes classification.