Attention mechanisms and transfer learning for robust peach leaf damage classification under domain shift

ArXi:2606.02045v1 Announce Type: cross Artificial intelligence provides a practical framework for crop damage assessment from imagery data, ing early decision-making in agricultural management. In peach orchards, climate change increases abiotic stress and biotic pressures, including pests and diseases, which often produce visually similar foliar symptoms. This overlap makes manual diagnosis difficult, especially across multiple fields with varying environmental conditions, highlighting the need for automated models with strong generalization ability.