High-altitude insulator defect detection algorithm based on improved SSD
According to the poor detection effect caused by the complex background of high-altitude insula-tors and the small defect target,an improved small-target detection algorithm based on Residual Fusion At-tention Module(RFAM-SSD)is proposed.Firstly,the network is divided into two parts.The backbone network obtains the feature layer through the Multiple Cycle Feature Fusion Module(ResNet Multiple Cycle Feature Fusion Module,RES-MFCFM)of the residual network,and six predictive feature layers are ob-tained through convolution.The branch network obtains the corresponding six feature layers through convo-lution,while the two branches obtain the final six feature layers through RFAM to detect the target.Focal-1OU Loss is designed to replace the original loss and improve the detection effect.Experiments show that the mAP of the improved algorithm is 92.4％,which is 7.2％higher than that of the original SSD algorithm,and meets the real-time detection requirements,indicating that the detection algorithm has a good detection effect on small insulator defect targets.
small target detectionSSD algorithmresidual networkattention mechanismfeature fusion
万方数据
维普
