Attention-based pretrained deep learning framework for nutrient deficiency diagnosis in oilseed rape using UAV multispectral imagery

Key Points

• Diagnosis of nutrient deficiency is achieved with an attention-based deep learning framework, improving accuracy.
• The model utilized UAV multispectral imagery for effective identification of nutrient issues in the crops.
• Assessment employed a pretrained model to leverage existing knowledge for enhanced learning and prediction.
• Implementing this framework may enable faster, more efficient detection of crop health issues, supporting better agricultural practices.