• Laser & Optoelectronics Progress
  • Vol. 56, Issue 21, 211505 (2019)
Jingming Chen, Jie Jin*, and Weifeng Wang
Author Affiliations
  • School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China
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    DOI: 10.3788/LOP56.211505 Cite this Article Set citation alerts
    Jingming Chen, Jie Jin, Weifeng Wang. Improved Algorithm Based on Feature Pyramid Networks[J]. Laser & Optoelectronics Progress, 2019, 56(21): 211505 Copy Citation Text show less

    Abstract

    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 are predicted, and the multi-scale and multi-stage prediction is realized finally. On the premise that the network parameters are 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 VOC07+12, which has good detection performance.
    Jingming Chen, Jie Jin, Weifeng Wang. Improved Algorithm Based on Feature Pyramid Networks[J]. Laser & Optoelectronics Progress, 2019, 56(21): 211505
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