  We proposed a new modeling method to promote the performance of prohibited
items recognition via X-ray image. We analyzed the characteristics of
prohibited items and X-ray images. We found the fact that the scales of some
items are too small to be recognized which encumber the model performance. Then
we adopted a set of data augmentation and modified the model to adapt the field
of prohibited items recognition. The Convolutional Block Attention Module(CBAM)
and rescoring mechanism has been assembled into the model. By the modification,
our model achieved a mAP of 89.9% on SIXray10, mAP of 74.8%.
