A convolutional neural network to identify mosquito species (Diptera: Culicidae) of the genus Aedes by wing images
Accurate species identification is crucial to assess the medical relevance of a mosquito specimen, but requires intensive experience of the observers and well-equipped laboratories. In this proof-of-concept study, we developed a convolutional neural network (CNN) to identify seven Aedes species by wing images, only. While previous studies used images of the whole mosquito body, the nearly two-dimensional wings may facilitate standardized image capture and reduce the complexity of the CNN implementation. The mean macro F1 score to predict the Aedes species was 90% for grayscale images and 91% for RGB images. In conclusion, wing images are sufficient to identify mosquito species by CNNs.
Sauer, F.G., Werny, M., Nolte, K. et al. A convolutional neural network to identify mosquito species (Diptera: Culicidae) of the genus Aedes by wing images. Sci Rep 14, 3094 (2024). https://doi.org/10.1038/s41598-024-53631-x