An annotated image dataset for training mosquito species recognition system on human skin.

ABSTRACT: This paper introduces a new mosquito images dataset that is suitable for training and evaluating a recognition system on mosquitoes in normal or smashed conditions. The images dataset served mainly for the development a machine learning model that can recognize the mosquito in the public community, which commonly found in the smashed/damaged form by human. Especially the images of mosquito in hashed condition, which to the best of our knowledge, a dataset that fulfilled such condition is not available. There are three mosquito species in the dataset, which are Aedes aegypti, Aedes albopictus and Culex quinquefasciatus, and the images were annotated until species level due to the specimen was purely bred in a WHO accredited breeding laboratory. The dataset consists of seven root files, six

SUBMITTER: Ong SQ 

PROVIDER: S-EPMC9287291 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature