  Marine vessel re-identification technology is an important component of
intelligent shipping systems and an important part of the visual perception
tasks required for marine surveillance. However, unlike the situation on land,
the maritime environment is complex and variable with fewer samples, and it is
more difficult to perform vessel re-identification at sea. Therefore, this
paper proposes a transfer dynamic alignment algorithm and simulates the swaying
situation of vessels at sea, using a well-camouflaged and similar warship as
the test target to improve the recognition difficulty and thus cope with the
impact caused by complex sea conditions, and discusses the effect of different
types of vessels as transfer objects. The experimental results show that the
improved algorithm improves the mean average accuracy (mAP) by 10.2% and the
first hit rate (Rank1) by 4.9% on average.
