The invention discloses a green channel vehicle cargo carrying
radioactive source image recognition method based on a
convolutional neural network. The method comprises the following steps: step 1, preprocessing a green channel vehicle cargo carrying
radioactive source image; 2, preparing an input image sample; step 3, designing a green channel vehicle cargo carrying
radioactive source image recognition model; step 4, optimizing the green channel vehicle cargo carrying radioactive
source image identification model; and step 5, by training, verifying and testing the model and recording changesof a
loss function and classification accuracy in the training process, the
loss function can reflect the capacity of the model for accurately classifying the cargo types. According to the invention,the green channel vehicle carried cargo radioactive
source image identification based on the
convolutional neural network is adopted, so that subjective dependence of an inspection result on inspection personnel can be avoided, and the working intensity of front-line inspection personnel is reduced. And meanwhile, the inspection efficiency can be improved, and the congestion condition of the tollstation is reduced.