  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.
