FORTRESS combines depthwise separable convolutions and a gated Kolmogorov-Arnold module to report F1 of 0.771 and mIoU of 0.677 on the CSDD benchmark, but the core KAN contribution is not isolated by ablation.
Co-cracksegment: A new collaborative deep learning framework for pixel-level semantic segmentation of concrete cracks,
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FORTRESS: Function-composition Optimized Real-Time Resilient Structural Segmentation via Kolmogorov-Arnold Enhanced Spatial Attention Networks
FORTRESS combines depthwise separable convolutions and a gated Kolmogorov-Arnold module to report F1 of 0.771 and mIoU of 0.677 on the CSDD benchmark, but the core KAN contribution is not isolated by ablation.