A convolutional neural network to identify mosquito species (Diptera: Culicidae) of the genus Aedes by wing images.

ABSTRACT: 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. Mosquitoes were sampled from different sites in Germany. Their wings were mounted and photographed with a professional stereomicroscope. The data set consisted of 1155 wing images from seven Aedes species as well as 554 wings from different non-Aedes mosquitoes. A CNN was trained to differe

SUBMITTER: Sauer FG 

PROVIDER: S-EPMC10850211 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature