most citedDeepDamageNet: A two-step deep-learning model for multi-disaster building damage segmentation and classification using satellite imagery

11 citations · 11 across the 1 of their papers we have counts for

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cs.CV2024★ 11 cited

DeepDamageNet: A two-step deep-learning model for multi-disaster building damage segmentation and classification using satellite imagery

Irene Alisjahbana, Jiawei Li, Ben +2

Satellite imagery has played an increasingly important role in post-disaster building damage assessment. Unfortunately, current methods still rely on manual visual interpretation,…