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UID:0-7745@eng.ufl.edu
DTSTART;TZID=America/New_York:20250918T125000
DTEND;TZID=America/New_York:20250918T134000
DTSTAMP:20250908T142433Z
URL:https://www.eng.ufl.edu/news-events/events/seminar-automation-and-deep
 -learning-to-advance-digital-agriculture/
SUMMARY:Seminar : Automation and Deep Learning to Advance Digital Agricultu
 re
DESCRIPTION:To sustainably intensify agricultural production and food suppl
 y while preserving the environment\, we must radically improve the efficie
 ncy and resilience of our agri-food systems through automation and AI-driv
 en digital agriculture. In this talk\, I will go over multiple research pr
 ojects that leverage agricultural robotics and deep learning to address ch
 allenges 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 syst
 em is empowered by machine learning-based vision intelligence\, including 
 object detection and semantic/instance segmentation for detecting plants a
 nd plant parts in 2D images\, video frame-based multi-object tracking for 
 plant organ counting\, and 3D deep learning models for point cloud segment
 ation and architectural trait extraction. Another project will highlight a
  patented sensor to emulate berry fruit and quantify mechanical impacts du
 ring the mechanical harvesting and postharvest handling processes\, as wel
 l as a deep learning-based hyperspectral imaging approach for berry intern
 al bruise detection and quantification.
CATEGORIES:Seminars
LOCATION:MAE-A Room 303\, 939 Sweetwater Drive\, Gainesville\, FL\, 32611\,
  United States
GEO:29.643814;-82.34865
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=939 Sweetwater Drive\, Gain
 esville\, FL\, 32611\, United States;X-APPLE-RADIUS=100;X-TITLE=MAE-A Room
  303:geo:29.643814,-82.34865
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