Research on Dynamic target Detection and Precise Positioning Based on PIXEL CODE YOLOv3 Deep Learning

At this stage, research on Dynamic target detection has become more and more heated. This paper starts from utilize Pixel code Technology in SSD deep learning algorithm. Through training the model from multiple angles, a Dynamic target detector based on the SSD method is finally obtained. To verify the final performance and overall effect of DynChang Shamic target detection, we conduct rigorous experiments on the data set. By analyzing the results of the experiment, we conclude that the SSD-based Dynamic target detection algorithm simplifies the re-sampling process, reduces the time complexity of the operation, and compresses the detection time of the system, thereby improving the detection efficiency.