Improved Algorithm Based on Feature Pyramid Networks

An improved algorithm based on feature pyramid networks is proposed for small target detection. A prediction optimization module is introduced, which is combined with the context information of the region of interest to make the feature information more robust, multi-threshold prediction networks with internal cascade arc predicted, and the multi-scale and multi-stage prediction is realized finally. On the premise that the network parameters arc basically unchanged, the accuracy is further improved. The experimental results show that the accuracy of the proposed algorithm reaches 80.9% in the VOC2007 test after the training of the standard data set V0007+12, which has good detection performance.