The deadline to submit a session, town hall, or pre-conference workshop proposal for AGU25 has passed. Please search for and review proposed sessions below. Please note this site is frozen as of 4/29/25 and will not reflect any changes to proposals made after this date.


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Abstract: Efficient Corn Disease Monitoring via Polarized Imaging and Self-Supervised Deep Learning (AGU25)

Efficient Corn Disease Monitoring via Polarized Imaging and Self-Supervised Deep Learning

Grace Vincent1, Michael Kudenov2, Ralph Dean3, Peter Balint-Kurti4 and Cranos Williams2, (1)North Carolina State University Raleigh, Electrical and Computer Engineering, Raleigh, NC, United States, (2)North Carolina State University Raleigh, Electrical and Computer Engineering, Raleigh, United States, (3)North Carolina State University Raleigh, Entomology and Plant Pathology, Raleigh, United States, (4)USDA-ARS Plant Science Research Unit, Raleigh, United States
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