  In this paper, we present a ship detection pipeline for low-cost medium
resolution satellite optical imagery obtained from ESA Sentinel-2 and Planet
Labs Dove constellations. This optical satellite imagery is readily available
for any place on Earth and underutilized in the maritime domain, compared to
existing solutions based on synthetic-aperture radar (SAR) imagery. We
developed a ship detection method based on a state-of-the-art
deep-learning-based object detection method which was developed and evaluated
on a large-scale dataset that was collected and automatically annotated with
the help of Automatic Identification System (AIS) data.
