Disaster Assessment from Satellite Imagery by Analysing Topographical Features Using Deep Learning-Reference-Cited by-同舟云学术

Disaster Assessment from Satellite Imagery by Analysing Topographical Features Using Deep Learning

Published:2020-03-20 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2020 2nd International Conference on Image, Video and Signal Processing
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Author:

Dotel Saramsha¹,Shrestha Avishekh¹,Bhusal Anish¹,Pathak Ramesh¹,Shakya Aman¹,Panday Sanjeeb Prasad¹

Affiliation:

1. Institute of Engineering, Tribhuvan University, Pulchowk, Lalitpur, Nepal

Funder

University Grants Commission- Nepal

Publisher

ACM

Reference20 articles.

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2. Voigt S. Giulio F. T. etal 2016. Global trends in satellite-based emergency mapping. Science. 353. 247--252. DOI: https://dx.doi.org/10.1126/science.aad8728 Voigt S. Giulio F. T. et al. 2016. Global trends in satellite-based emergency mapping. Science. 353. 247--252. DOI: https://dx.doi.org/10.1126/science.aad8728

3. Voigt S. Kemper T. Riedlinger T. Kiefl R. Scholte K. and Mehl H. 2007. Satellite Image Analysis for Disaster and Crisis-Management Support. IEEE T. Geoscience and Remote Sensing. 45. 1520--1528. DOI: https://dx.doi.org/10.1109/TGRS.2007.895830 Voigt S. Kemper T. Riedlinger T. Kiefl R. Scholte K. and Mehl H. 2007. Satellite Image Analysis for Disaster and Crisis-Management Support. IEEE T. Geoscience and Remote Sensing. 45. 1520--1528. DOI: https://dx.doi.org/10.1109/TGRS.2007.895830

4. Trekin A. Novikov G. Potapov G. Ignatiev V. and Burnaev E. 2018. Satellite Imagery Analysis for Operational Damage Assessment in Emergency Situations. arXiv:1803.00397. Retrieved from: https://arxiv.org/abs/1803.00397 Trekin A. Novikov G. Potapov G. Ignatiev V. and Burnaev E. 2018. Satellite Imagery Analysis for Operational Damage Assessment in Emergency Situations. arXiv:1803.00397. Retrieved from: https://arxiv.org/abs/1803.00397

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