Betel Leaf Disease Classification Under Limited Data Using ConvNeXt-Tiny and UCB-Guided Adaptive Augmentation
Automated betel leaf disease recognition remains challenging under limited and imbalanced data conditions. This study investigates an Upper Confidence Bound (UCB)-guided adaptive augmentation framework for the classification of healthy leaves, leaf rot, and leaf spot. To reduce the risk of performance inflation caused...