| Description: |
Our method, UAV-CrackSeg, aims to improve road crack segmentation in complex backgrounds.
1. Architecture: We use Segformer-b1 as the baseline and introduce the SimAM (Simple Attention Module) parameter-free attention mechanism to enhance feature extraction for fine cracks.
2. Loss Function: A hybrid loss function combining CrossEntropyLoss (1.0) and LovaszLoss (1.0) is designed to optimize boundary connectivity.
3. Strategy: We apply a multi-model weighted fusion strategy to boost the final IoU score.
[Model Weights]
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