Interface Identification of Automatic Verification System Based on Deep Learning

Automatic verification system is the future trend in the metrological verification field. However, it is still a problem waiting to be solved that the system can automatically recognize instrument interfaces with different models and can record data. Based on YOLOv3 deep learning algorithm, this paper shoots and makes instrument interface data sets independently. In addition, the network model training is conducted under the PaddlePaddle framework. On the LabView platform, the encapsulation model has designed that the automatic verification system instrument interface recognition module is used by automatic verification system. Through real machine tests, the instrument interface recognition module can effectively identify the instrument interface to be checked and can identify multiple data windows, indicating that the method can meet the tasks of instrument interface recognition in the automatic verification system.