  Monitoring large areas is presently feasible with high resolution drone
cameras, as opposed to time-consuming and expensive ground surveys. In this
work we reveal for the first time, the potential of using a state-of-the-art
change detection GAN based algorithm with high resolution drone images for
infrastructure inspection. We demonstrate this concept on solar panel
installation. A deep learning, data-driven algorithm for identifying changes
based on a change detection deep learning algorithm was proposed. We use the
Conditional Adversarial Network approach to present a framework for change
detection in images. The proposed network architecture is based on pix2pix GAN
framework. Extensive experimental results have shown that our proposed approach
outperforms the other state-of-the-art change detection methods.
