Open-source machine learning BANTER acoustic classification of beaked whale echolocation pulses-Reference-Cited by-同舟云学术

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Open-source machine learning BANTER acoustic classification of beaked whale echolocation pulses

Published:2024-05 Issue: Volume:80 Page:102511
ISSN:1574-9541
Container-title:Ecological Informatics
language:en
Short-container-title:Ecological Informatics

Author:

Rankin Shannon,Sakai Taiki,Archer Frederick I.,Barlow Jay,Cholewiak Danielle,DeAngelis Annamaria I.,McCullough Jennifer L.K.,Oleson Erin M.,Simonis Anne E.,Soldevilla Melissa S.,Trickey Jennifer S.

Funder

US Navy

Bureau of Ocean Energy Management

Publisher

Elsevier BV

Reference47 articles.

1. Unique morphological and acoustic characteristics of beaked whales (Mesoplodon Sp.) off the west coast of Baja California, Mexico;Barlow;Mar. Mamm. Sci.,2022

2. Acoustic-based estimates of Cuvier’s beaked whale (Ziphius Cavirostris) density and abundance along the u.s. west coast from drifting hydrophone recorders;Barlow;Mar. Mamm. Sci.,2022

3. Species-specific beaked whale echolocation signals;Baumann-Pickering;J. Acoust. Soc. Am.,2013

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Machine learning with taxonomic family delimitation aids in the classification of ephemeral beaked whale events in passive acoustic monitoring;PLOS ONE;2024-06-04

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