Fig. 11
From: An enhanced deep learning-based framework for diagnosing apple leaf diseases
Representative samples showing images before (left) and after (right) augmentation. Augmentation variants include rotation, brightness/contrast adjustments, cropping/translation, and mild blur/noise to simulate environmental variation. These transformations increase visual diversity and help the detector learn robustness to viewpoint, illumination, and minor occlusion.
