Species‐level image classification with convolutional neural network enables insect identification from habitus images

Changes in insect biomass, abundance, and diversity are challenging to track at sufficient spatial, temporal, and taxonomic resolution. Camera traps can capture habitus images of ground‐dwelling insects. However, currently sampling involves manually detecting and identifying specimens. Here, we test...

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Veröffentlicht in:	Ecology and evolution 2020-01, Vol.10 (2), p.737-747
Hauptverfasser:	Hansen, Oskar L. P., Svenning, Jens‐Christian, Olsen, Kent, Dupont, Steen, Garner, Beulah H., Iosifidis, Alexandros, Price, Benjamin W., Høye, Toke T.
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy arthropod sampling Arthropods Artificial neural networks automatic species identification Beetles Body size camera trap Cameras Classification Data collection Datasets Ecological monitoring Ecology entomological collection Environmental changes Environmental Sciences & Ecology Evolutionary Biology Genera Habitus Identification Image classification image database Insects Life Sciences & Biomedicine Methods Museums Neural networks Original Research Recall Science & Technology Species Species classification Taxonomy Trapping
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