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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
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Research@WUR
Dataset . 2022
Data sources: Research@WUR
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https://doi.org/10.5281/zenodo...
Dataset . 2022
License: CC BY
Data sources: Sygma
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OPTIMA - RGB colour images and multispectral images (including LabelImg annotations)

Authors: Blok, Pieter M.; Polder, Gerrit; Peller, Joseph; van Daalen, Tim;

OPTIMA - RGB colour images and multispectral images (including LabelImg annotations)

Abstract

The images and annotations (LabelImg) in this folder are acquired during the H2020 OPTIMA project. The images were acquired in orchards, vineyards and fields in three European countries (France, Italy, Spain). The images represent three diseases in three crops: apple scab in apple, alternaria in carrot, downy mildew in grape. The txt files contain the bounding box locations for the diseases (bounding box detection for YOLOv5 object detection). The folder contains three subfolders: apple_applescab ms: multispectral images acquired on 10-05-2022 in Spain with the Silios multispectral camera rgb: rgb colour images acquired on 27-05-2021 and 10-06-2021 in Spain with the NEON-202B-JT2-X smart-camera carrot_alternaria ms: multispectral images acquired on 23-09-2021 and 24-09-2021 in France with the Silios multispectral camera rgb: rgb colour images acquired on 02-09-2021, 24-09-2021, and 04-11-2021 in France with the NEON-201B-JT2-X smart-camera grape_downymildew ms: multispectral images acquired on 06-06-2019 in Italy with the IMEC multispectral camera rgb: rgb colour images acquired on 23-07-2021 in Italy with the NEON-201B-JT2-X smart-camera

Country
Netherlands
Related Organizations
Keywords

rgb, yolov5, bounding box, multispectral, smart-camera, deep learning, object detection

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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