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Open Access

Peer-reviewed

Research Article

From manual counting to YOLO: Using computer vision to automate large-scale fecundity assays in C. elegans

Linyao Peng ,

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: kqq8ng@virginia.edu, linyaopeng25@gmail.com

Affiliation Department of Biology, University of Virginia, Charlottesville, Virginia, United States of America

https://orcid.org/0000-0002-7435-9900

⨯
Hongyi Shui,

Roles Formal analysis, Software, Validation

Affiliation Department of Integrated Marketing Communications, Northwestern University, Evaston, Illinois, United States of America
⨯
Anne Nicole Janisch,

Roles Data curation, Investigation, Methodology

Affiliation Department of Biology, University of Virginia, Charlottesville, Virginia, United States of America
⨯
Sarah Dede Hesse,

Roles Data curation, Investigation, Methodology

Affiliation Department of Biology, University of Virginia, Charlottesville, Virginia, United States of America
⨯
Victoria Kathleen Feist,

Roles Data curation, Investigation, Methodology

Affiliation Department of Biology, University of Virginia, Charlottesville, Virginia, United States of America
⨯
Amanda Kyle Gibson

Roles Funding acquisition, Methodology, Supervision

Affiliation Department of Biology, University of Virginia, Charlottesville, Virginia, United States of America
⨯

From manual counting to YOLO: Using computer vision to automate large-scale fecundity assays in C. elegans

Linyao Peng,
Hongyi Shui,
Anne Nicole Janisch,
Sarah Dede Hesse,
Victoria Kathleen Feist,
Amanda Kyle Gibson

x

Published: July 30, 2026
https://doi.org/10.1371/journal.pone.0354821

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Computer vision
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Caenorhabditis elegans
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Computer imaging
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Fecundity
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Deep learning
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