Method / resourcemodel-written summary

The method achieved average recall of 0.868 using 1% of the training dataset.

A claim from Root segmentation of X-ray computed tomography images of container horticultural plants using Mask R-CNN and DBSCAN-based 3D point cloud clustering · 2023

Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

The method achieved average recall of 0.868 using 1% of the training dataset.

Taxon
poinsettias and onionsAllium cepaEuphorbia pulcherrimae0
Outcome
recalle0
Value
0.868e0

Not reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorSettingDirectionQualifier

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Allium cepa
Allium cepa · TaxonMehdi · CC BY-SA 3.0 · Wikimedia Commons ↗
Euphorbia pulcherrima
Euphorbia pulcherrima · TaxonFrank Vincentz · CC BY-SA 3.0 · Wikimedia Commons ↗

Verbatim

e0

“The proposed method was evaluated on scans of poinsettias and onions and achieved average scores of 0.734, 0.868, 0.794, and 0.669 for precision, recall, dice, and IoU, respectively, utilizing only 1% of the training dataset.”

✓ located verbatim in the source · abstract, characters 1398–1623

Title

Root segmentation of X-ray computed tomography images of container horticultural plants using Mask R-CNN and DBSCAN-based 3D point cloud clustering

Mary Elizabeth Cassity; Paul C Bartley; Yin Bao 2023 Omaha, Nebraska July 9-12, 2023 2023. doi:10.13031/aim.202301147

Other claims from this paper (4)

Record rev-e6ed9437fbff66d90f4407553b8d112083ba69f5185273323cffa61618498820 · schema claims-v0.9 · position 2 in the model’s answer