Comprehensive Semantic Segmentation on High Resolution UAV Imagery for Natural Disaster Damage Assessment

2 Sep 2020Maryam RahnemoonfarTashnim ChowdhuryRobin MurphyOdair Fernandes

In this paper, we present a large-scale hurricane Michael dataset for visual perception in disaster scenarios, and analyze state-of-the-art deep neural network models for semantic segmentation. The dataset consists of around 2000 high-resolution aerial images, with annotated ground-truth data for semantic segmentation... (read more)

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