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For: Stowell D. Computational bioacoustics with deep learning: a review and roadmap. PeerJ 2022;10:e13152. [PMID: 35341043 DOI: 10.7717/peerj.13152] [Cited by in Crossref: 29] [Cited by in F6Publishing: 26] [Article Influence: 29.0] [Reference Citation Analysis]
Number Citing Articles
1 Gómez-gómez J, Vidaña-vila E, Sevillano X. Western mediterranean wetland birds dataset: A new annotated dataset for acoustic bird species classification. Ecological Informatics 2023. [DOI: 10.1016/j.ecoinf.2023.102014] [Reference Citation Analysis]
2 Jonsson T. Micro-CT and deep learning: Modern techniques and applications in insect morphology and neuroscience. Front Insect Sci 2023;3. [DOI: 10.3389/finsc.2023.1016277] [Reference Citation Analysis]
3 Zambolli AH, Manzano MCR, Honda LK, Rezende GC, Culot L. Performance of autonomous recorders to detect a cryptic and endangered primate species, the black lion-tamarin (Leontopithecus chrysopygus). Am J Primatol 2023;85:e23454. [PMID: 36415048 DOI: 10.1002/ajp.23454] [Reference Citation Analysis]
4 Sethi SS, Bick A, Ewers RM, Klinck H, Ramesh V, Tuanmu M, Coomes DA. Is there an accurate and generalisable way to use soundscapes to monitor biodiversity?. [DOI: 10.1101/2022.12.19.521085] [Reference Citation Analysis]
5 Bergler C, Smeele SQ, Tyndel SA, Barnhill A, Ortiz ST, Kalan AK, Cheng RX, Brinkløv S, Osiecka AN, Tougaard J, Jakobsen F, Wahlberg M, Nöth E, Maier A, Klump BC. ANIMAL-SPOT enables animal-independent signal detection and classification using deep learning. Sci Rep 2022;12:21966. [PMID: 36535999 DOI: 10.1038/s41598-022-26429-y] [Reference Citation Analysis]
6 Aodha OM, Martínez Balvanera S, Damstra E, Cooke M, Eichinski P, Browning E, Barataud M, Boughey K, Coles R, Giacomini G, Swiney G. MCM, Obrist MK, Parsons S, Sattler T, Jones KE. Towards a General Approach for Bat Echolocation Detection and Classification.. [DOI: 10.1101/2022.12.14.520490] [Reference Citation Analysis]
7 Araya-salas M, Smith-vidaurre G, Chaverri G, Brenes JC, Chirino F, Elizondo-calvo J, Rico-guevara A. ohun: an R package for diagnosing and optimizing automatic sound event detection.. [DOI: 10.1101/2022.12.13.520253] [Reference Citation Analysis]
8 Provost KL, Yang J, Carstens BC. The impacts of fine-tuning, phylogenetic distance, and sample size on big-data bioacoustics. PLoS One 2022;17:e0278522. [PMID: 36477744 DOI: 10.1371/journal.pone.0278522] [Reference Citation Analysis]
9 Savagian A, Riehl C. Group chorusing as an intragroup signal in the greater ani, a communally breeding bird. Ethology 2022. [DOI: 10.1111/eth.13345] [Reference Citation Analysis]
10 Conant PC, Li P, Liu X, Klinck H, Fleishman E, Gillespie D, Nosal EM, Roch MA. Silbido profundo: An open source package for the use of deep learning to detect odontocete whistles. J Acoust Soc Am 2022;152:3800. [PMID: 36586843 DOI: 10.1121/10.0016631] [Reference Citation Analysis]
11 Rycyk A, Bolaji DA, Factheu C, Kamla Takoukam A. Using transfer learning with a convolutional neural network to detect African manatee (Trichechus senegalensis) vocalizations. JASA Express Lett 2022;2:121201. [PMID: 36586963 DOI: 10.1121/10.0016543] [Reference Citation Analysis]
12 Besson M, Alison J, Bjerge K, Gorochowski TE, Høye TT, Jucker T, Mann HMR, Clements CF. Towards the fully automated monitoring of ecological communities. Ecol Lett 2022;25:2753-75. [PMID: 36264848 DOI: 10.1111/ele.14123] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
13 Michaud F, Sueur J, Le Cesne M, Haupert S. Unsupervised classification to improve the quality of a bird song recording dataset. Ecological Informatics 2022. [DOI: 10.1016/j.ecoinf.2022.101952] [Reference Citation Analysis]
14 Lapp S, Larkin JL, Parker HA, Larkin JT, Shaffer DR, Tett C, Mcneil DJ, Fiss CJ, Kitzes J. Automated recognition of ruffed grouse drumming in field recordings. Wildlife Society Bulletin 2022. [DOI: 10.1002/wsb.1395] [Reference Citation Analysis]
15 Gatto BB, Colonna JG, dos Santos EM, Lameiras Koerich A, Fukui K. Discriminative Singular Spectrum Classifier with applications on bioacoustic signal recognition. Digital Signal Processing 2022. [DOI: 10.1016/j.dsp.2022.103858] [Reference Citation Analysis]
16 Morales G, Vargas V, Espejo D, Poblete V, Tomasevic JA, Otondo F, Navedo JG. Method for passive acoustic monitoring of bird communities using UMAP and a deep neural network. Ecological Informatics 2022. [DOI: 10.1016/j.ecoinf.2022.101909] [Reference Citation Analysis]
17 Manzano R, Bota G, Brotons L, Soto-largo E, Pérez-granados C. Low-cost open-source recorders and ready-to-use machine learning approaches provide effective monitoring of threatened species. Ecological Informatics 2022. [DOI: 10.1016/j.ecoinf.2022.101910] [Reference Citation Analysis]
18 Cretois B, Rosten CM, Sethi SS. Voice activity detection in eco‐acoustic data enables privacy protection and is a proxy for human disturbance. Methods Ecol Evol. [DOI: 10.1111/2041-210x.14005] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
19 White EL, White PR, Bull JM, Risch D, Beck S, Edwards EWJ. More than a whistle: Automated detection of marine sound sources with a convolutional neural network. Front Mar Sci 2022;9:879145. [DOI: 10.3389/fmars.2022.879145] [Reference Citation Analysis]
20 Martin K, Adam O, Obin N, Dufour V. Rookognise: Acoustic detection and identification of individual rooks in field recordings using multi-task neural networks. Ecological Informatics 2022. [DOI: 10.1016/j.ecoinf.2022.101818] [Reference Citation Analysis]
21 Nolan V, Scott C, Yeiser JM, Wilhite N, Howell PE, Ingram D, Martin JA. The development of a convolutional neural network for the automatic detection of Northern Bobwhite Colinus virginianus covey calls. Remote Sens Ecol Conserv. [DOI: 10.1002/rse2.294] [Reference Citation Analysis]
22 Arnaud V, Pellegrino F, Keenan S, St-gelais X, Mathevon N, Levréro F, Coupé C. Improving the workflow to crack Small, Unbalanced, Noisy, but Genuine (SUNG) datasets in bioacoustics: the case of bonobo calls.. [DOI: 10.1101/2022.06.26.497684] [Reference Citation Analysis]
23 Clark FE, Dunn JC. From Soundwave to Soundscape: A Guide to Acoustic Research in Captive Animal Environments. Front Vet Sci 2022;9:889117. [DOI: 10.3389/fvets.2022.889117] [Reference Citation Analysis]
24 Lostanlen V, Cramer A, Salamon J, Farnsworth A, Van Doren BM, Kelling S, Bello JP. BirdVox: Machine listening for bird migration monitoring.. [DOI: 10.1101/2022.05.31.494155] [Reference Citation Analysis]
25 Martin K, Adam O, Obin N, Dufour V. Rookognise: Acoustic detection and identification of individual rooks in field recordings using multi-task neural networks.. [DOI: 10.1101/2022.02.19.481011] [Reference Citation Analysis]
26 Guerrero MJ, Restrepo J, Nieto-mora DA, Daza JM, Isaza C. Insights from Deep Learning in Feature Extraction for Non-supervised Multi-species Identification in Soundscapes. Advances in Artificial Intelligence – IBERAMIA 2022 2022. [DOI: 10.1007/978-3-031-22419-5_19] [Reference Citation Analysis]