The present invention discloses a
deep learning-based insulator identification method. The insulator identification method comprises the steps of pre-
processing an
aerial image, and secondly, extending the data via the methods, such as the
geometric transformation, the
contrast enhancement, an analog
noise adding method, etc.; acquiring the insulator samples, aiming at the insulators of different types, classifying to acquire; determining a to-be-trained model structure; inputting the samples in the to-be-trained model, and continuously adjusting the weights and the bias parameters by the
forward propagation and
backward propagation methods, and finally determining an optimal
model parameter, based on the trained model, taking a to-be-detected image as an input
signal, and by the network multi-layer
convolution,
pooling and full-connection operations, obtaining a final detection identification result. According to the present invention, by a
deep learning method, the insulator characteristics are learned continuously, a
learning network model is determined, the different insulators are identified under different background environments, and support is provided for the
electric power maintenance decisions.