Zero-shot instance segmentation for plant phenotyping in vertical farming with foundation models and VC-NMS

This study addresses the critical issue of scarce annotated data in vertical farming by developing a zero-shot segmentation framework. The integration of domain-specific indices (NCGI) and prompt optimization techniques provides an effective solution for plant phenotyping, highlighting the potential of weakly supervised models in agricultural computer vision where extensive manual annotation is impractical.