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RaspberrySet: Dataset of Annotated Raspberry Images for Object Detection

Authors: Strautiņa, Sarmīte; Kalniņa, Ieva; Kaufmane, Edīte; Sudars, Kaspars; Namatēvs, Ivars; Ņikuļins, Artūrs; Judvaitis, Jānis; +1 Authors

RaspberrySet: Dataset of Annotated Raspberry Images for Object Detection

Abstract

RaspberrySet contains annotated images of the Raspberries (Rubus idaeus). The images were captured in the four development stages. The 2039 images in the dataset have a resolution of 1773 x 1773 pixels and were taken by iPhone XS. The annotation was carried out with the help of LabelImg software (version 1.8.6) manually be the experts. Annotations are presented in YOLO format. The dataset has five classes, which are Bud, Flower, Unripe Berry, Ripe Berry and Damaged buds. Out of 46659 annotations present in the dataset 11788 was for Buds, 4748 for Flowers, 29156 for Unripe Berries, 463 for Ripe Berries and 504 for Damaged Buds. The images were captured on the site at the Institute of Horticulture in Dobele, Latvia.

Keywords

Deep learning, Object detection, High-throughput phenotyping, Precise agriculture

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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.
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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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