Existing deep-learning methods have achieved remarkable performance in recognizing in-laboratory plant disease images.
However, their performance often significantly degrades in classifying in-the-wild images.
Furthermore, we observed that in-the-wild plant images may exhibit similar appearances across various diseases (i.e., small inter-class discrepancy) while the same diseases may look quite different (i.e., large intra-class variance).
Motivated by this observation, we propose an… See the full description on the dataset page:
https://huggingface.co/datasets/uqtwei2/PlantWild.
