Deep Learning Helps to Map Mars and Analyze its Surface Chemistry

UMass Amherst computer scientist leads team using new techniques to handle huge data sets Student Marie Ozanne, left, and astronomy professor Darby Dyar, who serves on the scientific mission team for the Mars Curiosity rover, use a laser-plus-spectrometer instrument. Courtesy Mount Holyoke College. AMHERST, Mass. – Researchers at the University of Massachusetts Amherst and Mount Holyoke College are teaming up to apply recent advances in machine learning, specifically biologically inspired deep learning methods, to analyze large amounts of scientific data from Mars. They are funded by a new four-year, $1.2 million National Science Foundation grant to computer scientist Sridhar Mahadevan, lead principal investigator at UMass Amherst’s College of Information and Computer Sciences. His co-investigators are Mario Parente, an expert in analysis of hyperspectral images at UMass Amherst, and Darby Dyar…


Link to Full Article: Deep Learning Helps to Map Mars and Analyze its Surface Chemistry