Automation and Deep Learning to Advance Digital Agriculture
Abstract: To sustainably intensify agricultural production and food supply while preserving the environment, we must radically improve the efficiency and resilience of our agri-food systems through automation and AI-driven digital agriculture. In this talk, I will go over multiple research projects that leverage agricultural robotics and deep learning to address challenges spanning the food chain from breeding to harvest and postharvest handling. I will present a novel modular agricultural robotic system (MARS) that is an autonomous, multi-purpose, and affordable robotic platform for in-field automated phenotyping and precision farming. The robotic system is empowered by machine learning-based vision intelligence, including object detection and semantic/instance segmentation for detecting plants and plant parts in 2D images, video frame-based multi-object tracking for plant organ counting, and 3D deep learning models for point cloud segmentation and architectural trait extraction. Another project will highlight a patented sensor to emulate berry fruit and quantify mechanical impacts during the mechanical harvesting and postharvest handling processes, as well as a deep learning-based hyperspectral imaging approach for berry internal bruise detection and quantification.
Date and Time
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- 939 Sweetwater Dr
- University of Florida
- GAINESVILLE, Florida
- United States 32611
- Building: MAE-A
- Room Number: 303
- Click here for Map
- Contact Event Host
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John Schueller, Gainesville Section IEEE Vice Chair, schuejk@ufl.edu
Eric Schwartz, Gainesville Section IEEE Chair, ems@ufl.edu
- Co-sponsored by UF MAE Department
Speakers
Dr. Changying "Charlie" Li of Agricultural and Biological Engineering Department
Automation and Deep Learning to Advance Digital Agriculture
Biography:
Charlie Li is a Professor in the Agricultural and Biological Engineering Department and the IFAS AI Administrative Coordinator since 2023. Prior to his current position, he was a Professor and Distinguished Faculty Scholar at the College of Engineering at the University of Georgia. He earned his doctoral degree in Agricultural and Biological Engineering from the Pennsylvania State University and received his postdoctoral research training at the University of Illinois at Urbana-Champaign. He has 25 years of experience in developing innovative AI-based sensing and automation technologies to advance digital agriculture and automated phenotyping. He is a Fellow of the American Society of Agricultural and Biological Engineers (ASABE) and a member of the Institute of Electrical and Electronics Engineers (IEEE). His work has been recognized by several national awards from the ASABE. Together with his collaborators, he has published over 130 peer-reviewed journal papers and secured more than $17 million in grant funding from a diverse range of sources.
Email:
Address:285 Frazier Rogers Hall, University of Florida, Gainesville, Florida, United States, 32611