Deep Learning Based Classification for Hoverflies (Diptera: Syrphidae)




Syrphidae is essential in pollinating many flowering plants and cereals and is a family with high species diversity in the order Diptera. These family species are also used in biodiversity and conservation studies. This study proposes an image-based CNN model for easy, fast, and accurate identification of Syrphidae species. Seven hundred twenty-seven hoverfly images were used to train and test the developed deep-learning model. Four hundred seventy-nine of these images were allocated to the training set and two hundred forty-eight to the test dataset. There are a total of 15 species in the dataset. With the CNN-based deep learning model developed in this study, accuracy 0.96, precision 0.97, recall 0.96, and f-measure 0.96 values were obtained for the dataset. The experimental results showed that the proposed CNN-based deep learning model had a high success rate in distinguishing the Syrphidae species.




How to Cite

Utku, A., Ayaz, Z., Çiftçi, D., & Akcayol, M. A. (2023). Deep Learning Based Classification for Hoverflies (Diptera: Syrphidae). Journal of the Entomological Research Society, 25(3), 529–544.



Journal of the Entomological Research Society