Deep learning-based aerial image segmentation with open data for disaster impact assessment

Author:

Gupta Ananya,Watson Simon,Yin Hujun

Funder

University of Manchester

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference44 articles.

1. Multi-source data fusion based on ensemble learning for rapid building damage mapping during the 2018 Sulawesi Earthquake and Tsunami in Palu, Indonesia;Adriano;Remote Sensing,2019

2. N. Audebert, B.L. Saux, S. Lefèvre, Semantic Segmentation of Earth Observation Data Using Multimodal and Multi-scale Deep Networks (9 2016), http://arxiv.org/abs/1609.06846.

3. RoadTracer: automatic extraction of road networks from aerial images;Bastani;Computer Vision and Pattern Recognition,2018

4. Post-disaster map builder: Crowdsensed digital pedestrian map construction of the disaster affected areas through smartphone based DTN;Bhattacharjee;Computer Communications,2019

5. Remote Sensing Role in Emergency Mapping for Disaster response;Boccardo,2015

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