Automatic identification of medically important mosquitoes using embedded learning approach-based image-retrieval system.

ABSTRACT: Mosquito-borne diseases such as dengue fever and malaria are the top 10 leading causes of death in low-income countries. Control measure for the mosquito population plays an essential role in the fight against the disease. Currently, several intervention strategies; chemical-, biological-, mechanical- and environmental methods remain under development and need further improvement in their effectiveness. Although, a conventional entomological surveillance, required a microscope and taxonomic key for identification by professionals, is a key strategy to evaluate the population growth of these mosquitoes, these techniques are tedious, time-consuming, labor-intensive, and reliant on skillful and well-trained personnel. Here, we proposed an automatic screening, namely the deep metric learning a

SUBMITTER: Kittichai V 

PROVIDER: S-EPMC10313673 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature