Automated Feature Extraction for the Geospatial Professional

RMS 6280 3 Quarter Hours
Course Level CPS - Graduate
Description Offers an introduction to machine learning and its use in image interpretation and automated feature extraction. Explores a variety of techniques and work flows associated with collecting features of interest from multiple data sources such as aerial and satellite imagery, as well as from light detection and ranging (LIDAR) and elevation data. Offers students an opportunity for hands-on experience using the software; to learn how to solve real-life problems in exercises that correspond to the concepts being introduced; and to learn how to create industry-standard products and processing models for automation. Covers the fundamentals of machine learning, supervised and unsupervised classification, hierarchical learning, postprocessing, cleanup, automation, modeling, and publication.


Students should refer to the CPS Prerequisite Table for course prerequisite and corequisite information.


Course Sections

There are no current sections scheduled for this course. Undergraduate course numbers changed beginning with the Fall 2016 term. Please make sure you are using the current course number.
Next Term Starts
  • Winter Graduate
    Jan 8, 2018 (6- and 12-week classes)
    Feb 19, 2018 (6-week classes)

Academic Calendar

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