An unmanned aerial vehicle (UAV) technology for estimating leaf N content in rice crops, from multispectral imagery
Proof of concept delivered. Three machine learning methods based on multivariable linear regressions (MLR), support vector machines (SVM), and neural networks (NN), were applied and compared through the entire phonological cycle of the crop: vegetative (V), reproductive (R), and ripening (Ri).
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| Main Author: | |
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| Format: | Report biblioteca |
| Language: | English |
| Published: |
2020-12-31
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| Subjects: | rice, crops, technology, development, rural development, methods, learning, networks, systems, agrifood systems, machine learning, imagery, ripening, multispectral imagery, neural networks, vectors, |
| Online Access: | https://hdl.handle.net/10568/122306 |
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