130 citations · 133 across the 13 of their papers we have counts for
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3D Semantic Segmentation for Post-Disaster Assessment
Nhut Le, Maryam Rahnemoonfar
The increasing frequency of natural disasters poses severe threats to human lives and leads to substantial economic losses. While 3D semantic segmentation is crucial for post-disas…
Think First, Assign Next (ThiFAN-VQA): A Two-stage Chain-of-Thought Framework for Post-Disaster Damage Assessment
Ehsan Karimi, Nhut Le, Maryam Rahnemoonfar
Timely and accurate assessment of damages following natural disasters is essential for effective emergency response and recovery. Recent AI-based frameworks have been developed to…
3DAeroRelief: The first 3D Benchmark UAV Dataset for Post-Disaster Assessment
Nhut Le, Ehsan Karimi, Maryam Rahnemoonfar
Timely assessment of structural damage is critical for disaster response and recovery. However, most prior work in natural disaster analysis relies on 2D imagery, which lacks depth…
ZeShot-VQA: Zero-Shot Visual Question Answering Framework with Answer Mapping for Natural Disaster Damage Assessment
Ehsan Karimi, Maryam Rahnemoonfar
Natural disasters usually affect vast areas and devastate infrastructures. Performing a timely and efficient response is crucial to minimize the impact on affected communities, and…