By Ruth Taylor

July 20, 2021

News from: Publications

Bioacoustic monitoring with machine learning (ML) models can provide valuable insights for informed decision-making in conservation efforts. In this study, the team built deep convolutional neural networks to analyze field recordings and classify calls of regionally rare bird species. Limited training data is a challenge for model running on rare species. This study describes the use of transfer learning, data augmentation, and K-fold cross validation to improve species presence survey results.

For the DOI, click here.

To view the project website, click here.

 

Acoustic detection of regionally rare bird species through deep convolutional neural networks