Research on improved text detection algorithm for prosecutorial scenarios based on DBNet
In the text detection of inspection scene,the existing detection algorithms still have the problems of high false detec-tion rate and high missing detection rate.By improving the existing feature extraction network,introducing the efficient channel at-tention and spatial attention module CBAM,and improving the differentiable binary function,the improved network is applied to the text detection of inspection scene.The accuracy,recall and F value of the improved algorithm on ICDAR 2015 data set in-creased by 2.2,5.4 and 4.2 percentage,respectively,to 89.2%,63.6%and 74.3%compared with those before the improvement.Ex-perimental data show that the improved DBNet text detection algorithm has a significant improvement in convergence speed and de-tection accuracy.
text detectionprosecutorial scenessifferentiable binarizationdeep learningCBAM
NETL
NSTL
万方数据
