Interpreting atomization of agricultural spray image patterns using latent Dirichlet allocation techniques
Breakup patterns of agricultural formulations are explored using unsupervised learning techniques to elucidate the mechanics of atomization for oil-in-water formulations. Previous researchers have shown these formulations succumb to a different breakup mechanism than conventional formulations, begin...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2020-01-01
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| Series: | Artificial Intelligence in Agriculture |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2589721720300313 |