Year: 2018
Type: conference-paper
Abstract: Mars is the fourth planet from the sun and the second smallest planet in the solar system after Mercury. Like Earth, Mars has a range of surface features such as valleys, deserts, and polar ice caps. Scientists around the globe have developed a specific interest in the terrain and climate of Mars because it is believed to have the potential to host life. To assist scientists to discover past or present life on Mars, we developed machine learning models (based on deep learning) to analyze the satellite images received from the Red Planet. The models automatically eliminated satellite images that were of a low quality and subsequently classified the high-quality images based on climate/environmental conditions. The models were tested on sample datasets and demonstrated the ability to achieve considerable accuracy. We also integrated additional functionality to convert two-dimensional (2D) satellite images into an informative (3D) format for better analysis and exploration. Furthermore, the solution was integrated into a mobile application that can be used by scientists and members of the public who are interested in space science.
Institution: United Arab Emirates University
Language: English
Subfield: Astronomy and Astrophysics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W2945796468