Ecological inferences about marine mammals from passive acoustic data
Monitoring on the basis of sound recordings, or passive acoustic monitoring, can
complement or serve as an alternative to real‐time visual or aural monitoring of marine …
complement or serve as an alternative to real‐time visual or aural monitoring of marine …
NOAA and BOEM minimum recommendations for use of passive acoustic listening systems in offshore wind energy development monitoring and mitigation programs
SM Van Parijs, K Baker, J Carduner, J Daly… - Frontiers in Marine …, 2021 - frontiersin.org
Offshore wind energy development is rapidly ram** up in United States (US) waters in
order to meet renewable energy goals. With a diverse suite of endangered large whale …
order to meet renewable energy goals. With a diverse suite of endangered large whale …
A convolutional neural network for automated detection of humpback whale song in a diverse, long-term passive acoustic dataset
Passive acoustic monitoring is a well-established tool for researching the occurrence,
movements, and ecology of a wide variety of marine mammal species. Advances in …
movements, and ecology of a wide variety of marine mammal species. Advances in …
Deep learning algorithm outperforms experienced human observer at detection of blue whale D‐calls: a double‐observer analysis
An automated algorithm for passive acoustic detection of blue whale D‐calls was developed
based on established deep learning methods for image recognition via the DenseNet …
based on established deep learning methods for image recognition via the DenseNet …
BioCPPNet: automatic bioacoustic source separation with deep neural networks
PC Bermant - Scientific Reports, 2021 - nature.com
Abstract We introduce the Bioacoustic Cocktail Party Problem Network (BioCPPNet), a
lightweight, modular, and robust U-Net-based machine learning architecture optimized for …
lightweight, modular, and robust U-Net-based machine learning architecture optimized for …
Underwater acoustic signal classification based on sparse time–frequency representation and deep learning
For classification of underwater acoustic signals, we propose a novel sparse anisotropic
chirplet transform (ACT) to reveal fine time-frequency structures. The signal features in the …
chirplet transform (ACT) to reveal fine time-frequency structures. The signal features in the …
[HTML][HTML] Deep embedded clustering of coral reef bioacoustics
Deep clustering was applied to unlabeled, automatically detected signals in a coral reef
soundscape to distinguish fish pulse calls from segments of whale song. Deep embedded …
soundscape to distinguish fish pulse calls from segments of whale song. Deep embedded …
Detecting, classifying, and counting blue whale calls with Siamese neural networks
M Zhong, M Torterotot, TA Branch… - The Journal of the …, 2021 - pubs.aip.org
The goal of this project is to use acoustic signatures to detect, classify, and count the calls of
four acoustic populations of blue whales so that, ultimately, the conservation status of each …
four acoustic populations of blue whales so that, ultimately, the conservation status of each …
Establishing baselines for predicting change in ambient sound metrics, marine mammal, and vessel occurrence within a US offshore wind energy area
Evaluating potential impacts on marine animals or increased sound levels resulting from
offshore wind energy construction requires the establishment of baseline data records from …
offshore wind energy construction requires the establishment of baseline data records from …
[HTML][HTML] Performance metrics for marine mammal signal detection and classification
Automatic algorithms for the detection and classification of sound are essential to the
analysis of acoustic datasets with long duration. Metrics are needed to assess the …
analysis of acoustic datasets with long duration. Metrics are needed to assess the …