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Optimal Hyperspectral Narrowbands for Discriminating Agricultural Crops

机译：区分农作物的最佳高光谱窄带

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摘要

The main goal of this paper was to establish the best hyperspectral narrowbands for discriminating agricultural crops and to determine the accuracy with which such discrimination was possible. Six crops (wheat, barley, chickpea, lentil, vetch, and cumin) were studied. The best 12 narrowbands provided the most rapid increase in spectral discrimination. Further addition of oarrowbands, only marginally increased discrimination capability reaching a plateau around 30 narrowbands. The overall accuracy (and K_(hat)) in separating the six crops increased rapidly from 73/100 (K_(hat) = 71) when 6 best bands were used to 84/100 (K_(hat) = 79) when 12 best bands were used.
机译：本文的主要目的是建立最佳的高光谱窄带来区分农作物，并确定这种区分的准确性。研究了六种作物（小麦，大麦，鹰嘴豆，小扁豆，紫v和小茴香）。最佳的12条窄带在频谱辨别力方面提供了最快的增长。进一步增加了窄带，仅略微提高了分辨能力，达到了约30个窄带的平稳状态。当使用6条最佳条带时，分离六种作物的总体准确度（和K_（hat）= 73/100（K_hat = 71））迅速提高到使用12条最佳条带时的84/100（K_hat = 79）。乐队被使用。

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