Automated Bird Species Identification Using Neural Networks

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Vemula Omkarini, G. Krishna Mohan


Birds are the warm-blooded vertebrates constituting of class Aves, there are nearly 10 thousand living species of birds in the world with multifarious characteristics and appearances. Bird watching is often considered to be an interesting hobby by human beings in the natural environment. The human knowledge over the species isn’t enough to identify a species of bird accurately, as it requires lot of expertise in the field of Ornithology. This paper presents an automated model based on the deep neural networks which automatically identifies the species of a bird given as the test data set. The model was trained and tested for 253 species of birds with the total images 7637 and 1853 images for train and test respectively and the model has shown a promising accuracy of 98% when tested with the test datasets.

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Vemula Omkarini, G. Krishna Mohan. (2021). Automated Bird Species Identification Using Neural Networks. Annals of the Romanian Society for Cell Biology, 25(6), 5402–5407. Retrieved from