Evaluating Computer Vision and Augmented Reality Guidance to Optimize Weapon Training Safety and Performance.

The first real-world data collection enhanced the existing computer vision models (80:20 train-test split), and the updated models resulted in perfect detection of 134 mortar rounds fired during that session.

In the first training event, there were 13 false positives (e.g., because of false detection during mortar tube cleaning).

After assessment the team developed a model to detect mortar cleaning and was able to detect all 32 cleaning evolutions recorded at the sites with one false positive.