IntelinAir - Monitoring Forest and Waterbody Health from Remote Sensing Imagery
 Closed for Registration
  • Lecture time: Tuesday: 15:30:00 - 16:20:00 ET
  • Lab time: Thursday: 15:30:00 - 17:20:00 ET
  • Domain: Digital Agriculture
  • Keywords: Agriculture, Big Data, Computer Vision, Deep Learning, Forestry, Remote Sensing, Sustainability
  • Tools: Agritech Industry Specifics, AWS, Docker, Git, Python, Pytorch, Tensorflow
  • Citizenship: Open to all students
Summary

The focus of this project is around assessing and monitoring the health of forests and waterbodies by using multispectral imagery combined with public data sources to produce better analysis.

Description

Please see the PDF for a detailed project description. When registering for this project in UniTime, look for 'IntelinAir' in the Note section, and select the appropriate CRN.

AY 2022 - 2023 Last updated: June 14, 2022, 7:50 a.m.