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Knowledge-Guided Vision-Language Inference for Image-Based Urban Flood Depth Estimation
Timely floodwater depth estimates support road accessibility assessment and emergency response during urban flooding. Supervised vision methods often require extensive labeled datasets, while recent foundation vision-language models (VLMs) offer flexible visual reasoning but can inconsistently yield
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