@inproceedings{803cce05abda4e99bad78b64d4a69762,
title = "Estimating Displaced Populations from Overhead",
abstract = "We introduce a deep learning approach to perform fine-grained population estimation for displacement camps using high-resolution overhead imagery. We train and evaluate our approach on drone imagery cross-referenced with population data for refugee camps in Cox's Bazar, Bangladesh in 2018 and 2019. Our proposed approach achieves 7.41\% mean absolute percent error on sequestered camp imagery. We believe our experiments with real-world displacement camp data constitute an important step towards the development of tools that enable the humanitarian community to effectively and rapidly respond to the global displacement crisis.",
keywords = "CNN, Deep Learning, Machine Learning, Population Estimation, Regression, Remote Sensing",
author = "Armin Hadzic and Gordon Christie and Jeffrey Freeman and Amber Dismer and Stevan Bullard and Ashley Greiner and Nathan Jacobs and Ryan Mukherjee",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 ; Conference date: 26-09-2020 Through 02-10-2020",
year = "2020",
month = sep,
day = "26",
doi = "10.1109/IGARSS39084.2020.9324617",
language = "English",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1121--1124",
booktitle = "2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 - Proceedings",
}