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Correction: Double vision: 2D and 3D mosquito trajectories can be as valuable for behaviour analysis via machine learning

Parasites & Vectors volume 17, Article number: 326 (2024) Cite this article

The Original Article was published on 01 July 2024

Correction: Parasites & Vectors (2024) 17:282 https://doi.org/10.1186/s13071-024-06356-9


Following publication of the original article [1], it came to the attention of the authors that the article had published with an out-of-date graphical abstract. Namely, the graphical abstract detailed results that the article had prior to peer review. The article has since been updated with the correct, up-to-date version of the graphical abstract, which includes revised values for ROC AUC, updated ROC curves, and an amended UMAP figure. The authors thank you for reading this erratum and apologize for any inconvenience caused.

Reference

  1. Qureshi YM, Voloshin V, Towers CE, Covington JA, Towers DP. Double vision: 2D and 3D mosquito trajectories can be as valuable for behaviour analysis via machine learning. Parasit Vectors. 2024;17:282. https://doi.org/10.1186/s13071-024-06356-9.

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Authors and Affiliations

  1. School of Engineering, University of Warwick, Coventry, CV4 7AL, UK

    Yasser Mehmood Qureshi, Vitaly Voloshin, Catherine Elizabeth Towers, James Anthony Covington & David Peter Towers

  2. School of Biological and Behavioural Sciences, Queen Mary University of London, London, E1 4NS, UK

    Vitaly Voloshin

Authors
  1. Yasser Mehmood Qureshi
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  2. Vitaly Voloshin
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  3. Catherine Elizabeth Towers
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  4. James Anthony Covington
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  5. David Peter Towers
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Correspondence to Yasser Mehmood Qureshi.

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Qureshi, Y.M., Voloshin, V., Towers, C.E. et al. Correction: Double vision: 2D and 3D mosquito trajectories can be as valuable for behaviour analysis via machine learning. Parasites Vectors 17, 326 (2024). https://doi.org/10.1186/s13071-024-06410-6

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  • DOI: https://doi.org/10.1186/s13071-024-06410-6

Parasites & Vectors

ISSN: 1756-3305

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