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https://hdl.handle.net/2142/107271
Description
Title
Weed visualization
Author(s)
Varghese, Joshua
Contributor(s)
Chowdhary, Girish
Issue Date
2020-05
Keyword(s)
Agriculture
Deep learning
Computer vision
Abstract
Herbicide resistant weeds are becoming a problem in agriculture, causing millions of dollars’ worth
of losses each year. A possible approach to mechanical control of weeds would be a team of small
robots that are able to weed a given field in an algorithmic fashion. This research provides a suitable
simulation environment to model weed growth and a way to count weeds in video frames collected
by RGB cameras onboard the robots to estimate weed density, both of which will help develop a
data driven predictor that can estimate weed growth in a field given an initial seed bank density, in
the interest of creating a coordinated weeding policy.
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