A ResNet50 and YOLOv11 pipeline for tornado damage assessment reports 90.28% classification and 60.83% detection accuracy, but class imbalance and missing evaluation details weaken the result.
This approach enhances the model's ability to accurately detect damage across different contexts
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Accelerating Post-Tornado Disaster Assessment Using Advanced Deep Learning Models
A ResNet50 and YOLOv11 pipeline for tornado damage assessment reports 90.28% classification and 60.83% detection accuracy, but class imbalance and missing evaluation details weaken the result.