Pantograph Safe Trigger Target Real-Time Detection and Localization Method Based on Fused Differential Convolutional
Aiming at the problems of existing target detection algorithms,a real-time target detection and localization method based on fused differential convolution is proposed.Firstly,a backbone network with fused differential convolution is constructed to enhance feature extraction capabilities.Then,a feature fusion module and detection head with shared weights are designed to improve detection speed and accuracy.Finally,a multi-stage training strategy is formulated to further enhance accuracy.Experimental results on the pantograph detection dataset show that the proposed method achieves a frame detection speed of up to 149 frame/s on CPU hardware resources,with an whole mean average precision(mAP)of 81.20%.This is an improvement of 57 frame/s and 6 percentage points compared to the FemtoDet algorithm.Proposed method meets technical requirements for real-time and accurate triggering positioning tasks in high-speed railway scenarios.
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