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Dataset . 2023
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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Sim2real flower detection towards automated Calendula harvesting

Authors: Vierbergen, Wout; Willekens, Axel; Dekeyser, Donald; Cool, Simon; Wyffels, Francis;

Sim2real flower detection towards automated Calendula harvesting

Abstract

This dataset serves as supplementary material for the research paper titled 'Sim2real flower detection towards automated Calendula harvesting', which was published in the October 2023 issue of Biosystems Engineering. Within this upload, you will find a collection of both authentic and computer-generated images featuring Calendula (Calendula officinalis L.) flowers. Additionally, we have included the resources and original data utilized in generating the synthetic images. This dataset proves instrumental in demonstrating the successful transference of a deep neural network from simulation to real-world applications. The contents of this upload includes: Original RGB and depth images of Calendula flowers captured in a natural flower field, complete with bounding box annotations. The test data employed in our experiments. Unedited RGB images that were used in the photogrammetry pipeline. Three-dimensional models representing Calendula flowers. The resulting dataset of synthetic images. The synthetic dataset follows the Synthetic Optimized Labeled Objects (SOLO) Dataset Schema, as defined in the Unity Perception package. For completeness, the data scheme is also included in the upload. For more comprehensive details regarding this dataset and its associated metadata, we invite you to consult the published article in Biosystems Engineering, available at the following link: https://doi.org/10.1016/j.biosystemseng.2023.08.016.

Related Organizations
Keywords

Sim-to-real, Synthetic data, Calendula, Precision agriculture, Deep learning, Simulation

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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).
BIP!Citations provided by BIP!
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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