AI RESEARCH

Evaluating Few-Shot Pill Recognition Under Visual Domain Shift

arXiv CS.CV

ArXi:2603.10833v1 Announce Type: new Adverse drug events are a significant source of preventable harm, which has led to the development of automated pill recognition systems to enhance medication safety. Real-world deployment of these systems is hindered by visually complex conditions, including cluttered scenes, overlapping pills, reflections, and diverse acquisition environments. This study investigates few-shot pill recognition from a deployment-oriented perspective, prioritizing generalization under realistic cross-dataset domain shifts over architectural innovation.