Dual-stage histogram matching as normalization and augmentation improves ResNet-18 robustness for grapevine disease detection, with marked gains on heterogeneous canopy images.
Deep learning for the differentiation of downy mildew and spider mite in grapevine under field conditions
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Evaluating Histogram Matching for Robust Deep learning-Based Grapevine Disease Detection
Dual-stage histogram matching as normalization and augmentation improves ResNet-18 robustness for grapevine disease detection, with marked gains on heterogeneous canopy images.