Intelligent Detection Method to Improve Detection Accuracy for Power Signboard
The detection of power safety signs is an important component of the intelligent power safety operation control system.To improve the detection accuracy of safety signs in complex power scenarios,a power safety sign detection method based on improved YOLO was proposed.On the basis of YOLO,the network's prediction ability for small targets was improved by increasing the resolution of the prediction layer.In addition,the introduction of index pooling mechanism and the use of pooling masks to limit the introduction of useless information improved the accuracy of network classification and recognition.The experimental results show that the average accuracy of the improved detection network on the power sign test set reaches 75.2％,which is 3.2％higher than the conventional method.The proposed intelligent detection method can improve the detection and recognition ability of power signs,which is conducive to ensuring the safety of power production.
power signboarddeep learningobject detectionindex poolingnetwork identification
万方数据
维普
