Deep learning-based detection and classification of mosquitoes and Culicoides
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Issued Date
2026-01-01
Resource Type
ISSN
10946969
eISSN
19410123
Scopus ID
2-s2.0-105037856245
Journal Title
IEEE Instrumentation and Measurement Magazine
Rights Holder(s)
SCOPUS
Bibliographic Citation
IEEE Instrumentation and Measurement Magazine (2026)
Suggested Citation
Hongkajorn K., Wattanamethanont J., Unjit K., Vachmanus S., Kusakunniran W. Deep learning-based detection and classification of mosquitoes and Culicoides. IEEE Instrumentation and Measurement Magazine (2026). doi:10.1109/MIM.2025.11224861 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/116664
Title
Deep learning-based detection and classification of mosquitoes and Culicoides
Author's Affiliation
Corresponding Author(s)
Other Contributor(s)
Abstract
Mosquitoes and other small insects are important vectors of infectious diseases, making accurate identification of insect species essential for laboratory-based surveillance and entomological studies. Conventional identification methods rely on manual microscopic inspection, which is time-consuming, labor-intensive, and prone to human error, particularly when images contain multiple species in a single frame.