CSCI8523: AI for Earth: Monitoring Changes in the Environment via Deep Learning

3 CreditsField StudyOnline Available

Advances in machine learning in conjunction with massive amounts of data from Earth observing satellites offer huge potential for improving our understanding of how the Earth's environment and ecosystems have been changing and how they are being impacted by humans actions and changing climate. Deep learning approaches, that have had phenomenal success in the domain of computer vision and language/speech translation, hold promise in dealing with environmental problems. However, due to challenges that are unique to environmental applications, off-the-shelf deep learning techniques developed for related applications such as computer vision often have limited utility. This class will introduce to the students the promise and challenges in using deep learning techniques to analyze complex, multi-scale, spatio-temporal data for monitoring changes in the Earth and its environment on a global scale.Prerequisites: CSci 5523, CSci 5521, or equivalent

View on University Catalog

All Instructors

A- Average (3.764)Most Common: A (54%)

This total also includes data from semesters with unknown instructors.

24 students
FDCBA
  • 4.33

    /5

    Recommend
  • 4.83

    /5

    Effort
  • 4.50

    /5

    Understanding
  • 4.33

    /5

    Interesting
  • 4.50

    /5

    Activities


      Contribute on our Github

      Gopher Grades is maintained by Social Coding with data from Summer 2017 to Spring 2024 provided by the Office of Institutional Data and Research

      Privacy Policy