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

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 se...

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Veröffentlicht in:	arXiv.org 2020-09
Hauptverfasser:	Rahnemoonfar, Maryam, Chowdhury, Tashnim, Murphy, Robin, Fernandes, Odair
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Datasets High resolution Image resolution Image segmentation Natural disasters Semantic segmentation Semantics Visual perception
Online-Zugang:	Volltext
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