|
Characterization and classification method of burst pulses produced by Guiana dolphins (Sotalia guianensis) |
Mariana Barbosa, Lis Bittencourt, Tatiana Lemos Bisi, José Lailson-Brito & Alexandre F. Azevedo |
2022 |
1 |
69-80 |
|
Using autonomous recording units and change-point analysis to determine reproductive activity in an aerial insectivore |
Delaney R. Brooks & Joseph J. Nocera |
2022 |
2 |
208-218 |
|
Slope does not affect autonomous recorder detection shape: considerations for acoustic monitoring in forested landscapes |
Taylor Shaw, Sandra Müller & Michael Scherer-Lorenzen |
2022 |
3 |
261-282 |
|
BioAcoustic Index Tool: Long-term biodiversity monitoring using on-sensor acoustic index calculations |
David Kadish & Kasper Stoy |
2022 |
3 |
348-378 |
|
Software performance for the automated identification of bird vocalisations: the case of two closely related species |
Jean Marchal, François Fabianek & Yves Aubry |
2022 |
4 |
397-413 |
|
Development and test of a bat calls detection and classification method based on convolutional neural networks |
Y. Paumen, M. Mälzer, S. Alipek, J. Moll, B. Lüdtke & H. Schauer-Weisshahn |
2022 |
5 |
505-516 |
|
Assessing spontaneous howling rates in captive wolves using automatic passive recorders |
Vicente Palacios, Shannon M. Barber-Meyer, Bárbara Martí-Domken & Lori J. Schmidt |
2022 |
5 |
562-574 |
|
Tradition vs. innovation: comparing bioacoustics and mist-net results to bat sampling |
Matheus Camargo Silva Mancini, Frederico Hintze, Rafael de Souza Laurindo, Rodrigo de Macêdo Mello & Renato Gregorin |
2022 |
5 |
575-593 |
|
Book review: The Handbook of acoustic bat detection |
Krista Patriquin |
2022 |
6 |
740-742 |
|
Hidden Markov model for detection of mysticetes' vocalisations based on principal component analysis |
Olayinka O. Ogundile, Oluwaseyi P. Babalola, Seun G. Odeyemi & Kazeem I. Rufai |
2022 |
6 |
710-738 |
|
Automated bat call classification using deep convolutional neural networks |
E. Schwab, S. Pogrebnoj, M. Freund, F. Flossmann, S. Vogl & K.-H. Frommolt |
2023 |
1 |
1-16 |
|
Analysis of Mouse Vocal Communication (AMVOC): A deep, unsupervised method for rapid detection, analysis, and classification of ultrasonic vocalizations |
Vasiliki Stoumpou, César D. M. Vargas, Peter F. Schade, J. Lomax Boyd, Theodoros Giannakopoulos & Erich D. Jarvis |
2023 |
2 |
199-229 |
|
Automated Cataloguing of American silver perch (Bairdiella chrysoura) calls using machine learning |
DelWayne R. Bohnenstiehl |
2023 |
4 |
453-473 |
|
Passive Acoustic Monitoring in terrestrial vertebrates: a review |
Sebastian Hoefer, Donald T. McKnight, Slade Allen-Ankins, Eric J. Nordberg & Lin Schwarzkopf |
2023 |
5 |
506-531 |
|
Passive acoustic surveys and the BirdNET algorithm reveal detailed spatiotemporal variation in the vocal activity of two Anurans |
Connor M. Wood, Stefan Kahl, Stephanie Barnes, Rachel Van Horne & Cathy Brown |
2023 |
5 |
532-543 |
|
Chasing the bird: 3D acoustic tracking of aerial flight displays with a minimal planar microphone array |
Guillaume Dutilleux, Brett K. Sandercock & John Atle Kålås |
2023 |
6 |
622-641 |
|
Evaluating factors affecting species detection using passive acoustic monitoring in neotropical forests: a playback experiment |
Anja Hutschenreiter, J. Roberto Sosa-López, Fernando González-García & Filippo Aureli |
2023 |
6 |
660-678 |
|
The sound of hope: searching for critically endangered species using acoustic template matching |
C.B. De Araújo, J.P. Zurano, I.M.D. Torres, C.R.M.A. Simões, G.L.M. Rosa, A.G. Aguiar, W. Nogueira, H.A.L.S. Vilela, G. Magnago, B.T. Phalan & G.A. Zurita |
2023 |
6 |
708-723 |
|
Parselmouth for bioacoustics: automated acoustic analysis in Python |
Yannick Jadoul, Bart de Boer & Andrea Ravignani |
2024 |
1 |
1-19 |
|
Unsupervised discrimination of male Tawny owls (Strix aluco) individual calls using robust measurements of the acoustic signal |
Daniele Roccazzello, Orlando Tomassini, Elena Bernardini, Alessandro Massolo, Marco Dragonetti & Dimitri Giunchi |
2024 |
1 |
20-40 |
|
Tradeoffs in sound quality and cost for passive acoustic devices |
Clarissa A. Starbuck, Logan M. DeSchepper, Meredith L. Hoggatt & Joy M. O’Keefe |
2024 |
1 |
58-73 |
|
Audio data compression affects acoustic indices and reduces detections of birds by human listening and automated recognisers |
Alexander G. MacPhail, Daniel A. Yip, Elly C. Knight, Richard Hedley, Michelle Knaggs, Julia Shonfield, Emily Upham-Mills & Erin M. Bayne |
2024 |
1 |
74-90 |
|
The importance of acoustic background modelling in CNN-based detection of the Neotropical White-lored Spinetail (Aves, Passeriformes, Furnaridae) |
Thiago M. Ventura, Todor D. Ganchev, Cristian Pérez-Granados, Allan G. de Oliveira, Gabriel de S. G. Pedroso, Marinez I. Marques & Karl-L. Schuchmann |
2024 |
2 |
103-121 |
|
Field tests of small autonomous recording units: an evaluation of in-person versus automated point counts and a comparison of recording quality |
D. J. Mennill |
2024 |
2 |
157-177 |
|
Efficient quality assurance and quality control for passive acoustic monitoring data: reducing and documenting false-positive and false-negative errors |
Janine M. McManus, Barry G. Robinson & Steven L. Van Wilgenburg |
2024 |
2 |
178-202 |
