Automated Landform Detection On Mars Using Convolutional Neural Networks

Abstract

As the neighbor of Earth in the Solar System, Mars has been recognized as an important reference for investigating the evolution of history and future of Earth due to the similar rocky structure, water, thin atmosphere, earth-like elements and small molecule organic matter all been detected on Mars, which makes it a perfect candidate for our first interstellar settlement. Utilizing the large volume of public, high-resolution images of its surfaces we develop fully automated Deep Learning algorithms that serve exploring the planet. Convolutional Neural Networks(ConvNets) simulates human nerves. Through training, it operates as a feature extractor that detects and investigates various geological landforms on the surface of Mars; Its history and its resource reservoirs.