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Deep convolutional neural networks (CNNs) have outperformed existing objectrecognition and detection algorithms. On the other hand satellite imagerycaptures scenes that are diverse. This paper describes a deep learning approachthat analyzes a geo referenced satellite image and efficiently detects builtstructures in it. A Fully Convolution Network (FCN) is trained on lowresolution Google earth satellite imagery in order to achieve end result. Thedetected built communities are then correlated with the vaccination activitythat has furnished some useful statistics.

Using Satellite Imagery for Good: Detecting Communities in Desert and Mapping Vaccination Activities