12 citations · 15 across the 3 of their papers we have counts for
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cs.CV2022★ 3 cited
Crowdsourced-based Deep Convolutional Networks for Urban Flood Depth Mapping
Bahareh Alizadeh, Amir H. Behzadan
Successful flood recovery and evacuation require access to reliable flood depth information. Most existing flood mapping tools do not provide real-time flood maps of inundated stre…
cs.CV2021★ 12 cited
Feasibility study of urban flood mapping using traffic signs for route optimization
Bahareh Alizadeh, Diya Li, Zhe Zhang +1
Water events are the most frequent and costliest climate disasters around the world. In the U.S., an estimated 127 million people who live in coastal areas are at risk of substanti…