Monday, December 9 • 2:00pm - 2:45pm
Spotting Sustainability from Space: Detecting and Segmenting Agricultural Features in Satellite Imagery

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While technology can help farmers produce more while consuming less resources, also crucial to sustainability are tried-and-true conservation practices and geographic features leveraged to preserve waterways and prevent erosion.  In this session, we explore a proposal and proof of concept demonstrating how neural networks may be used to detect sustainable practices in agricultural fields.  From annotation to model training and image segmentation, learn how Mask RCNN was used to find sustainable features in four Iowa counties.

avatar for Rich Bellefeuille, MBA

Rich Bellefeuille, MBA

Director, Data Management, Land O'Lakes
Rich has a bachelor’s degree in Computer Science from St. Johns U. and an MBA from UMN Carlson School of Mgmt. He’s held various data-centric consulting positions and has 15 years’ experience in Agricultural and high-tech Medical Device industries.
avatar for Cort Lunke, MS

Cort Lunke, MS

Big Data Architect, Land O'Lakes, Inc.
Cort has spent seven years at Land O'Lakes, Inc in multiple roles including enterprise integration, big data architecture, and technology innovation. He is also an adjunct instructor in big data and AI at the University of St. Thomas.

Monday December 9, 2019 2:00pm - 2:45pm CST
Omnitheater (access via Floor 5 or 6) Science Museum of Minnesota, 120 W Kellogg Blvd, St. Paul, MN 55102