首页> 外国专利> 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

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

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.
机译:本公开内容提供了根据田地图像来测量田中农作物残留的系统和方法。特别地,本主题针对包括或以其他方式利用机器学习的作物残渣分类模型来至少部分地基于作物的此类部分的图像来确定田地的一部分的作物残渣参数值的系统和方法。成像设备捕获的视野。此外,可以执行主成分分析,例如将图像块投影到本征图像上,以减少提供给分类模型的特征向量的维数。

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