While they likely aren't the first things you think of when someone mentions space exploration, image recognition and machine learning are helping to push the human frontier further.

With over 60 known moons and majestic rings, Saturn has captivated scientists for hundreds of years. But many mysteries about Saturn's rings remain unsolved. Hoping to accelerate their understanding of the sixth planet from the Sun, NASA partnered with Topcoder to develop an algorithm to help them better understand ring structure and phenomena — and potentially find new moons that are not otherwise detectable by computers (due to false-positives).

Topcoder "atomized" the project into two distinct workstreams to arrive at a valuable solution, both of which involved real images captured by the Cassini spacecraft. The first challenge established a solid approach to solving the problem, which allowed the competitors in the second challenge to focus solely on the accuracy of their algorithmic solution.

The winning algorithm delivered by Topcoder was tested against more than 30,000 high-resolution Cassini images, and it identified 81% of previously identified propellers — gaps in the ring material created by "moonlets" that are smaller than known moons, but larger than other particles in the rings. To date, the algorithm has also identified four never-before-discovered propellers in the rings of Saturn.

With a new algorithmic solution, NASA is continuing to push the boundaries of interstellar exploration and discovery within the rings of Saturn and beyond.