Then the team leveraged deep learning to process the vast amount of imagery it collected from Maxar’s WorldView-3 satellite. In a matter of hours, the team collected its relevant data. This process usually takes months when sorting out by hand. On top of speed, the deep learning algorithms also provided consistent results less prone to error, as well as false negatives and false positives. In order to develop this method, the team created a customized training dataset of over 1,000 elephants, and then fed it into a Convolutional Neural Network (CNN). After trials, the team concluded that its CNN can detect elephants in satellite imagery with as high an accuracy as human detection capabilities.