A curated dataset and lightweight deep learning framework for tea leaf disease classification
Fig 2
Visual progression of the data pipeline.
Representative samples of Blight, Red Rust, Helopeltis, and Healthy classes showing raw field captures (left) alongside subsequent iterations of the dynamic augmentation pipeline (middle and right), which utilize stochastic rotations, horizontal flips, and brightness/contrast adjustments to enhance model generalization.