Bat detective-Deep learning tools for bat acoustic signal detection.

ABSTRACT: Passive acoustic sensing has emerged as a powerful tool for quantifying anthropogenic impacts on biodiversity, especially for echolocating bat species. To better assess bat population trends there is a critical need for accurate, reliable, and open source tools that allow the detection and classification of bat calls in large collections of audio recordings. The majority of existing tools are commercial or have focused on the species classification task, neglecting the important problem of first localizing echolocation calls in audio which is particularly problematic in noisy recordings. We developed a convolutional neural network based open-source pipeline for detecting ultrasonic, full-spectrum, search-phase calls produced by echolocating bats. Our deep learning algorithms were trained o

SUBMITTER: Mac Aodha O 

PROVIDER: S-EPMC5843167 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature