Kyle is a geographer in the Geospatial Sciences and Technologies branch at the Upper Midwest Environmental Sciences Center. His current work uses geospatial statistics and machine learning techniques to process aerial imagery for natural resource management.
Education:
M.S., Geography, The University of Tennessee, Knoxville, 2016
B.S., Ecological Restoration, Texas A&M University, 2014
Research Interests:
- Data Management
- Open Source Software
- Geographic Information Systems
- Machine Learning
- Cartography
Science and Products
Deep Learning for Automated Detection and Classification of Waterfowl, Seabirds, and other Wildlife from Digital Aerial Imagery
In collaboration with the Bureau of Ocean Energy Management, U.S. Fish and Wildlife Service, and the Vision Group at the International Computer Science Institute at the University of California - Berkeley, the U.S. Geological Survey Upper Midwest Environmental Sciences Center is developing deep learning algorithms and tools for the automatic detection, enumeration, classification, and annotation...
Science and Products
- Science
Deep Learning for Automated Detection and Classification of Waterfowl, Seabirds, and other Wildlife from Digital Aerial Imagery
In collaboration with the Bureau of Ocean Energy Management, U.S. Fish and Wildlife Service, and the Vision Group at the International Computer Science Institute at the University of California - Berkeley, the U.S. Geological Survey Upper Midwest Environmental Sciences Center is developing deep learning algorithms and tools for the automatic detection, enumeration, classification, and annotation... - Data
- Publications