Study reports multimodal AI arbitration improves plant-disease diagnosis in field imagery
An arXiv study combines two vision models with open-weight multimodal language models to resolve conflicting evidence in plant-disease images. The approach improved PlantDoc accuracy from 63.9% to 68.5% with Gemma, while tests on two Cornell robot-acquired datasets reached 98.9% and 99.3% accuracy. The researchers…