Dual-stage histogram matching as normalization and augmentation improves ResNet-18 robustness for grapevine disease detection, with marked gains on heterogeneous canopy images.
Next generation of computer vision for plant disease monitoring in precision agriculture: A contemporary survey, taxonomy, experi- ments, and future direction,
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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.