Variation in avian diversity in space and time is commonly used as a metric to assess
environmental changes. Conventionally, such data were collected by expert observers, but …

Rapid changes of the biosphere observed in recent years are caused by both small and
large scale drivers, like shifts in temperature, transformations in land-use, or changes in the …

Building accurate knowledge of the identity, the geographic distribution and the evolution of
species is essential for the sustainable development of humanity, as well as for biodiversity …

This paper addresses the problem of species classification in bird song recordings. The
massive amount of available field recordings of birds presents an opportunity to use …

Passive acoustic monitoring is a cornerstone of the assessment of ecosystem health and the
improvement of automated assessment systems has the potential to have a transformative …

Building accurate knowledge of the identity, the geographic distribution and the evolution of
species is essential for the sustainable development of humanity, as well as for biodiversity …

Accurate prediction of bird species from audio recordings is beneficial to bird conservation.
Thanks to the rapid advance in deep learning, the accuracy of bird species identification …

To protect tropical forest biodiversity, we need to be able to detect it reliably, cheaply, and at
scale. Automated detection of sound producing animals from passively recorded …

This paper presents deep learning techniques for audio-based bird identification in
soundscapes. Deep Convolutional Neural Networks are trained to classify 659 species …

Deep convolutional neural networks (DCNNs) have achieved breakthrough performance on
bird species identification using a spectrogram of bird vocalization. Aiming at the imbalance …