Day TG, Simpson JM, Razavi R, Kainz B (2023)
Publication Type: Journal article, Editorial
Publication year: 2023
Book Volume: 5
Pages Range: 335-336
Journal Issue: 4
DOI: 10.1038/s42256-023-00645-1
There is a continuing demand for high-quality, large-scale annotated datasets in medical imaging supported by machine learning. A new study investigates the importance of what type of instructions crowdsourced annotators receive.
APA:
Day, T.G., Simpson, J.M., Razavi, R., & Kainz, B. (2023). Improving image labelling quality. Nature Machine Intelligence, 5(4), 335-336. https://doi.org/10.1038/s42256-023-00645-1
MLA:
Day, Thomas G., et al. "Improving image labelling quality." Nature Machine Intelligence 5.4 (2023): 335-336.
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