电子器件2024，Vol.47Issue(4)：1027-1032,6.DOI:10.3969/j.issn.1005-9490.2024.04.024
基于监督和卷积循环神经网络算法的电力设备铭牌识别技术
Research on Power Equipment Nameplate Identification Technology Based on ASBNet-CRNN
摘要
Abstract
To solve the problem of difficult image feature extraction caused by the complex background of power equipment nameplate,a method for power equipment nameplate recognition based on supervised and convolutional recurrent neural network algorithm is proposed.Attention supervision based and back ground suppression segmentation network(ASBNet)algorithm is used for text detection,and a deep residual network is used as the backbone of the network.The attention mask forms multi-scale module features and fine-grained image features,and the background suppression module is used to improve the perception of text foreground and extract accurate nameplate image text boxes.The detected text boxes are input into the convolutional recurrent neural network(CRNN)for text recognition.The exper-imental results show that the proposed method outperforms the residual network(RestNet)and YOLOv3 computational models in terms of F-values by 7.56% and 10.38% respectively,indicating that the proposed method performs better in power equipment nameplate recognition.关键词
电力设备/ASBNet/CRNN/铭牌识别/深度残差网络Key words
power equipment/ASBNet/CRNN/nameplate recognition/deep residual networks分类
信息技术与安全科学引用本文复制引用
常荣,唐力..基于监督和卷积循环神经网络算法的电力设备铭牌识别技术[J].电子器件,2024,47(4):1027-1032,6.基金项目
云南电网有限责任公司科技项目(050400HK42220002) （050400HK42220002）
