Camouflage Target Detection Based on SSD Algorithm

Camouflage targets are highly integrated with the background, and there are problems of low detection accuracy and high detection difficulty with traditional detection methods. In this paper, the SSD network in one stage detection algorithm is applied to the detection of camouflage targets to explore the detection effect of using deep learning on camouflage targets, and it is validated on the military camouflage personnel dataset, and the experimental results show that the SSD algorithm can be well applied to the detection of camouflage targets with an average detection accuracy of 63.16%.