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Currently, most of the garbage classification target detection uses the YOLOv5 series algorithm, which has relatively low detection accuracy and detection speed for the same scale parameters and is difficult to meet the practical application requirements. The paper researches the application of garbage classification target detection based on PP-PicoDet technology, and compares it with several algorithms for experimental analysis; the results show that PP-PicoDet algorithm can achieve higher detection accuracy and speed with less number of parameters, and can meet the requirements of deployment on mobile devices.