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- W2022163301 abstract "The aim of this study was to select the best combination of filters for detecting various weed species located within carrot rows. In-field images were taken under artificial lighting with a multispectral device consisting of a black and white camera coupled with a rotating wheel holding 22 interference filters in the VIS-NIR domain. Measurements were performed over a period of 19 days, starting 1 week after crop emergence (early weeding can increase yields) and seven different weeds species were considered. The selection of the best filter combination was based on a quadratic discriminant analysis. The best combination of filters included three interference filters, respectively centred on 450, 550 and 700 nm. With this combination, the overall classification accuracy (CA) was 72%. When using only two filters, a slight degradation of the CA was noticed. When the classification results were reported on field images, a systematic misclassification of carrot cotyledons appears. Better results were obtained with a more advanced growth stage." @default.
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- W2022163301 date "2008-07-01" @default.
- W2022163301 modified "2023-10-16" @default.
- W2022163301 title "Selection of the most efficient wavelength bands for discriminating weeds from crop" @default.
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- W2022163301 doi "https://doi.org/10.1016/j.compag.2007.12.007" @default.
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