  The YOLOv3 target detection algorithm is widely used in industry due to its
high speed and high accuracy, but it has some limitations, such as the accuracy
degradation of unbalanced datasets. The YOLOv3 target detection algorithm is
based on a Gaussian fuzzy data augmentation approach to pre-process the data
set and improve the YOLOv3 target detection algorithm. Through the efficient
pre-processing, the confidence level of YOLOv3 is generally improved by
0.01-0.02 without changing the recognition speed of YOLOv3, and the processed
images also perform better in image localization due to effective feature
fusion, which is more in line with the requirement of recognition speed and
accuracy in production.
