Issue No. 06 - November/December (2007 vol. 22)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MIS.2007.114
Tomasz Stepinski , Lunar and Planetary Institute
Ricardo Vilalta , University of Houston
Soumya Ghosh , University of Colorado
The Mars planetary missions have produced vast stores of science data. The authors describe machine-learning methods and tools they've used to automate geomorphic mapping of Mars from archived data.
machine learning, Mars
S. Ghosh, T. Stepinski and R. Vilalta, "Machine Learning Tools for Automatic Mapping of Martian Landforms," in IEEE Intelligent Systems, vol. 22, no. , pp. 100-106, 2007.