Research on Digital Instrument Detection Method Based on Residual Network
Digital instrument is widely used in industrial applications and laboratory tests.Text detection plays an important role in the accuracy of digital instrument reading recognition,so it is of great significance to optimize the de-tection performance of text candidate box in the reading area.In order to obtain the reading text areas of different models and different kinds of digital instrument images,the standard residual structure with different number of convo-lution cores is designed based on the residual network.Then,the RegNet model set and DBNet model are combined to build the text detection model set,which has the advantages of fast,efficient and can be applied to most models of dig-ital instruments.The experiment shows that the improved detection model is better than the traditional model in many performance indicators,indicating that the network can accurately detect the text area of the digital instrument read-ing.
Deep learningInstrument detectionAdaptive thresholdText detection
万方数据
维普
