Object detection system based on SSD algorithm

摘要

SSD (Single Shot Multi Box Detector) is an object detection algorithm based on deep learning. As one of the most mainstream detection algorithms, it can greatly improve the detection speed and ensure the detection accuracy. In this paper, the Batch Norm operation is added to the network in order to improve the generalization of the network and speed up network training. The object counting function is added to the image recognition. This paper uses SSD algorithm that incorporates Batch Norm algorithm. The object detection system was built by the Flask framework and the Layui framework. The system can select the data to be detected on the front-end page, the detection results and the number of each type of object were displayed on the front-end page in real time.