Data from: Automated taxonomic identification of insects with expert-level accuracy using effective feature transfer from convolutional networks

Miroslav Valan, Karoly Makonyi, Atsuto Maki, Dominik Vondracek & Fredrik Ronquist
Rapid and reliable identification of insects is important in many contexts, from the detection of disease vectors and invasive species to the sorting of material from biodiversity inventories. Because of the shortage of adequate expertise, there has long been an interest in developing automated systems for this task. Previous attempts have been based on laborious and complex handcrafted extraction of image features, but in recent years it has been shown that sophisticated convolutional neural networks...
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These counts follow the COUNTER Code of Practice, meaning that Internet robots and repeats within a certain time frame are excluded.
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