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MEASURING CROP RESIDUE FROM IMAGERY USING A MACHINE-LEARNED CLASSIFICATION MODEL IN COMBINATION WITH PRINCIPAL COMPONENTS ANALYSIS
MEASURING CROP RESIDUE FROM IMAGERY USING A MACHINE-LEARNED CLASSIFICATION MODEL IN COMBINATION WITH PRINCIPAL COMPONENTS ANALYSIS
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机译:结合机器学习成分的机器学习分类模型从图像中测量作物残渣
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摘要
The present disclosure provides systems and methods that measure crop residue in a field from imagery of the field. In particular, the present subject matter is directed to systems and methods that include or otherwise leverage a machine-learned crop residue classification model to determine a crop residue parameter value for a portion of a field based at least in part on imagery of such portion of the field captured by an imaging device. Furthermore, principal components analysis, such as projecting image patches onto Eigen-images, can be performed to reduce the dimensionality of the feature vector provided to the classification model.
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