Saturated In-Domain, Separable Out-of-Domain: A Hierarchical Multi-Scale Lesion-Attention Network and a Zero-Shot Cross-Corpus Protocol for Multi-Crop Leaf Disease Classification
Leaf disease classifiers are ranked by held-out accuracy on their training corpus, where that number now exceeds 98% for many modern backbones. We ask what such a measurement can still resolve. On a four-crop, 21-class corpus of 7179 de-duplicated images, we train 26 architectures under one protocol with three seeds an...