Deep learning-based detection and classification of mosquitoes and Culicoides

Simple item page
dc.contributor.authorHongkajorn K.
dc.contributor.authorWattanamethanont J.
dc.contributor.authorUnjit K.
dc.contributor.authorVachmanus S.
dc.contributor.authorKusakunniran W.
dc.contributor.correspondenceHongkajorn K.
dc.contributor.otherMahidol University
dc.date.accessioned2026-05-11T18:14:52Z
dc.date.available2026-05-11T18:14:52Z
dc.date.issued2026-01-01
dc.description.abstractMosquitoes 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.
dc.identifier.citationIEEE Instrumentation and Measurement Magazine (2026)
dc.identifier.doi10.1109/MIM.2025.11224861
dc.identifier.eissn19410123
dc.identifier.issn10946969
dc.identifier.scopus2-s2.0-105037856245
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/123456789/116664
dc.rights.holderSCOPUS
dc.subjectPhysics and Astronomy
dc.subjectEngineering
dc.titleDeep learning-based detection and classification of mosquitoes and Culicoides
dc.typeArticle
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105037856245&origin=inward
oaire.citation.titleIEEE Instrumentation and Measurement Magazine
oairecerif.author.affiliationMahidol University
oairecerif.author.affiliationThailand National Institute of Animal Health

Files

Collections

Scopus 2026