Using Satellite Imagery for Good: Detecting Communities in Desert and Mapping Vaccination Activities
Year: 2017
Type: preprint
Abstract: Deep convolutional neural networks (CNNs) have outperformed existing object recognition and detection algorithms. On the other hand satellite imagery captures scenes that are diverse. This paper describes a deep learning approach that analyzes a geo referenced satellite image and efficiently detects built structures in it. A Fully Convolution Network (FCN) is trained on low resolution Google earth satellite imagery in order to achieve end result. The detected built communities are then correlated with the vaccination activity that has furnished some useful statistics.
Source: arXiv (Cornell University)
Authors: Shakeel, Anza, Ali, Mohsen
Language: English
Subfield: Ocean Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2613780225