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cs.CV2025
Knowledge-Guided Vision-Language Inference for Image-Based Urban Flood Depth Estimation
Zhangding Liu, Neda Mohammadi, John E. Taylor
Timely floodwater depth estimates support road accessibility assessment and emergency response during urban flooding. Supervised vision methods often require extensive labeled data…
cs.CV2025
MCANet: A Multi-Scale Class-Specific Attention Network for Multi-Label Post-Hurricane Damage Assessment Using UAV Imagery
Zhangding Liu, Neda Mohammadi, John E. Taylor
Hurricanes cause widespread damage to buildings, roads, and other infrastructure, making timely post-disaster damage assessment critical for emergency response and recovery plannin…
cs.CV2025
Multi-Label Classification Framework for Hurricane Damage Assessment
Zhangding Liu, Neda Mohammadi, John E. Taylor
Hurricanes cause widespread destruction, resulting in diverse damage types and severities that require timely and accurate assessment for effective disaster response. While traditi…