  This paper presents our contribution to the DeepGlobe Building Detection
Challenge. We enhanced the SpaceNet Challenge winning solution by proposing a
new fusion strategy based on a deep combiner using segmentation both results of
different CNN and input data to segment. Segmentation results for all cities
have been significantly improved (between 1% improvement over the baseline for
the smallest one to more than 7% for the largest one). The separation of
adjacent buildings should be the next enhancement made to the solution.
