Mosquito Wing Image Repository for Advancing Research on Geometric Morphometric- and AI-Based Identification

Nolte, K.; Agboli, E.; Azambuja Garcia, G.; Badolo, A.; Becker, N.; Do Huy, L.; Dworrak, T. V.; Eguchi, J.; Eisenbarth, A.; Maciel de Freitas, R.; Doumna-Ndalembouly, A. G.; Heitmann, A.; Jansen, S.; Joest, A.; Joest, H.; Kiel, E.; Meyer, A.; Pfitzner, W.-P.; Saathoff, J.; Schmidt-Chanasit, J.; Sulesco, T.; Tokatlian, A.; Velavan, T. P.; Villacanas de Castro, C.; Wehmeyer, M. L.; Zahouli, J.; Sauer, F. G.; Luehken, R.

doi:10.1101/2024.11.13.623340

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bioRxiv · 10.1101/2024.11.13.623340

Mosquito Wing Image Repository for Advancing Research on Geometric Morphometric- and AI-Based Identification

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Abstract

Accurate identification of mosquito species is essential for effective vector control and mitigation of mosquito-borne disease outbreaks. Traditional morphological identification requires highly specialized personnel and is time-consuming, while molecular techniques can be cost-effective and dependent on comprehensive genetic information. Wing geometric morphometry has emerged as a promising alternative, leveraging detailed geometric measurements of wing shapes and vein patterns to distinguish between species and detect intraspecies variations. This paper presents a curated dataset of 18,104 mosquito wing images, collected from 10,500 mosquito specimens, annotated with extensive meta-information, designed to support research in wing geometric morphometry and the development of machine learning models, ultimately supporting efforts in vector surveillance and research.

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Nolte, K., Agboli, E., Azambuja Garcia, G., Badolo, A., Becker, N., Do Huy, L., Dworrak, T. V., Eguchi, J., Eisenbarth, A., Maciel de Freitas, R., Doumna-Ndalembouly, A. G., Heitmann, A., Jansen, S., Joest, A., Joest, H., Kiel, E., Meyer, A., Pfitzner, W.-P., Saathoff, J., Schmidt-Chanasit, J., Sulesco, T., Tokatlian, A., Velavan, T. P., Villacanas de Castro, C., Wehmeyer, M. L., Zahouli, J., Sauer, F. G., Luehken, R.. 2024-11-15. Mosquito Wing Image Repository for Advancing Research on Geometric Morphometric- and AI-Based Identification. https://doi.org/10.1101/2024.11.13.623340

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