
Plants, Journal Year: 2025, Volume and Issue: 14(5), P. 786 - 786
Published: March 4, 2025
A novel eggplant disease detection method based on multimodal data fusion and attention mechanisms is proposed in this study, aimed at improving both the accuracy robustness of detection. The integrates image sensor data, optimizing features through an embedded mechanism, which enhances model’s ability to focus disease-related features. Experimental results demonstrate that excels across various evaluation metrics, achieving a precision 0.94, recall 0.90, 0.92, mAP@75 0.91, indicating excellent classification object localization capability. Further experiments, ablation studies, evaluated impact different loss functions model performance, all showed superior performance for approach. combined with mechanism effectively model, making it highly suitable complex identification tasks demonstrating significant potential widespread application.
Language: Английский