  The integration of artificial intelligence (AI) into military capabilities
has become a norm for major military power across the globe. Understanding how
these AI models operate is essential for maintaining strategic advantages and
ensuring security. This paper demonstrates an open-source methodology for
analyzing military AI models through a detailed examination of the Zhousidun
dataset, a Chinese-originated dataset that exhaustively labels critical
components on American and Allied destroyers. By demonstrating the replication
of a state-of-the-art computer vision model on this dataset, we illustrate how
open-source tools can be leveraged to assess and understand key military AI
capabilities. This methodology offers a robust framework for evaluating the
performance and potential of AI-enabled military capabilities, thus enhancing
the accuracy and reliability of strategic assessments.
