Nameplate text recognition model based on attention mechanism

Abstract

With the accelerating speed of power grid construction, the number of substations is increasing, and the management of power equipment is becoming more and more complex. The traditional manual management method is time-consuming, labor-consuming and inefficient. Due to the complex scene of power equipment nameplate, the failure of standardization of nameplate size, many characters, miscellaneous types and many steel seal information in the nameplate, the recognition accuracy of power nameplate needs to be improved. On the basis of fully mining the principle of attention mechanism encoder and decoder, combined with LSTM and convolutional neural network, this paper proposes a nameplate text recognition model based on attention mechanism to solve the problem of automatic nameplate text recognition. Experiments show that the method proposed in this paper can effectively identify the substation nameplate.