Data

Data for WeedScan manuscript

Commonwealth Scientific and Industrial Research Organisation
Schmidt-Lebuhn, Alexander
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25919/rcj3-5m69&rft.title=Data for WeedScan manuscript&rft.identifier=https://doi.org/10.25919/rcj3-5m69&rft.publisher=Commonwealth Scientific and Industrial Research Organisation&rft.description=Computer vision model, scripts, and test images for benchmarking test described in the manuscript WeedScan, a weed reporting system for Australia using an image classification model for identification.Lineage: The WeedScan model was trained by Ron Li (Data61) on an image dataset comprising ca. 195,000 images of 488 taxa of weeds and Australian native relatives using MMClassification on Bracewell. The Seek model was obtained from the v2.9.1 release on its Github. The test image library was collated by Alexander Schmidt-Lebuhn mostly from his own photographs but also donations from NSW DPI and John Hosking.&rft.creator=Schmidt-Lebuhn, Alexander &rft.date=2023&rft.edition=v1&rft_rights=Creative Commons Attribution-Noncommercial 4.0 Licence https://creativecommons.org/licenses/by-nc/4.0/&rft_rights=Data is accessible online and may be reused in accordance with licence conditions&rft_rights=All Rights (including copyright) CSIRO 2023.&rft_subject=Australia&rft_subject=weeds&rft_subject=AI&rft_subject=image classification&rft_subject=computer vision&rft_subject=WeedScan&rft_subject=Horticultural crop protection (incl. pests, diseases and weeds)&rft_subject=Horticultural production&rft_subject=AGRICULTURAL, VETERINARY AND FOOD SCIENCES&rft_subject=Plant and fungus systematics and taxonomy&rft_subject=Evolutionary biology&rft_subject=BIOLOGICAL SCIENCES&rft.type=dataset&rft.language=English Access the data
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Creative Commons Attribution-Noncommercial 4.0 Licence
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Data is accessible online and may be reused in accordance with licence conditions

All Rights (including copyright) CSIRO 2023.

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Computer vision model, scripts, and test images for benchmarking test described in the manuscript "WeedScan, a weed reporting system for Australia using an image classification model for identification".
Lineage: The WeedScan model was trained by Ron Li (Data61) on an image dataset comprising ca. 195,000 images of 488 taxa of weeds and Australian native relatives using MMClassification on Bracewell. The Seek model was obtained from the v2.9.1 release on its Github. The test image library was collated by Alexander Schmidt-Lebuhn mostly from his own photographs but also donations from NSW DPI and John Hosking.

Available: 2023-12-18

Data time period: 2020-11-01 to 2023-12-18

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Subjects
Agricultural, Veterinary and Food Sciences | AI | Australia | Biological Sciences | Evolutionary Biology | Horticultural Crop Protection (Incl. Pests, Diseases and Weeds) | Horticultural Production | Plant and Fungus Systematics and Taxonomy | WeedScan | computer vision | image classification | weeds |

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Identifiers
ACN 633 798 857