Cheng-Xuan Li

SAEFormer: Self-Supervised and Attention-Enhanced Efficient Transformer for Robust Tomato Leaf Disease Recognition

Tomato is a major global crop, yet foliar diseases seriously affect yield and quality. Accurate and efficient disease identification techniques are of great significance for ensuring agricultural production safety. To address the limitations of existing methods in feature extraction capability, model complexity, and de...