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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Automatic rain and cicada chorus filtering of bird acoustic data
Alexander Brown, Saurabh Garg, James Montgomery
Applied Soft Computing (2019) Vol. 81, pp. 105501-105501
Open Access | Times Cited: 32

Showing 1-25 of 32 citing articles:

Recent advances in intelligent recognition methods for fish stress behavior
Daoliang Li, Guangxu Wang, Ling Du, et al.
Aquacultural Engineering (2021) Vol. 96, pp. 102222-102222
Closed Access | Times Cited: 67
Systematic review of machine learning methods applied to ecoacoustics and soundscape monitoring
Daniel Alexis Nieto-Mora, Susana Rodríguez‐Buriticá, Paula Andrea Rodríguez Marín, et al.
Heliyon (2023) Vol. 9, Iss. 10, pp. e20275-e20275
Open Access | Times Cited: 20
Quantifying the Soundscape: How filters change acoustic indices
Emilia Hyland, Annie Schulz, John E. Quinn
Ecological Indicators (2023) Vol. 148, pp. 110061-110061
Open Access | Times Cited: 16
The combined effectiveness of acoustic indices in measuring bird species richness in biodiverse sites in Cyprus, China, and Australia
Christos Mammides, Pan Wuyuan, Guohualing Huang, et al.
Ecological Indicators (2025) Vol. 170, pp. 113105-113105
Open Access
Bioacoustic signal denoising: a review
Jie Xie, Juan G. Colonna, Jinglan Zhang
Artificial Intelligence Review (2020) Vol. 54, Iss. 5, pp. 3575-3597
Closed Access | Times Cited: 49
Automatic bioacoustics noise reduction method based on a deep feature loss network
Chengyun Zhang, Kaiying He, Xinghui Gao, et al.
Ecological Informatics (2024) Vol. 80, pp. 102517-102517
Open Access | Times Cited: 4
hardRain: An R package for quick, automated rainfall detection in ecoacoustic datasets using a threshold-based approach
Oliver C. Metcalf, Alexander Charles Lees, Jos Barlow, et al.
Ecological Indicators (2019) Vol. 109, pp. 105793-105793
Open Access | Times Cited: 38
Analysis of Soundscapes as an Ecological Tool
Renée P. Schoeman, Christine Erbe, Gianni Pavan, et al.
Springer eBooks (2022), pp. 217-267
Closed Access | Times Cited: 18
The Combined Effectiveness of Acoustic Indices in Measuring Bird Species Richness in Biodiverse Sites in Cyprus, China, and Australia
Christos Mammides, Pan Wuyuan, Guohualing Huang, et al.
(2024)
Closed Access | Times Cited: 3
Multi-Index Ecoacoustics Analysis for Terrestrial Soundscapes: A New Semi-Automated Approach Using Time-Series Motif Discovery and Random Forest Classification
Marina D. A. Scarpelli, Benoît Liquet, David Tucker, et al.
Frontiers in Ecology and Evolution (2021) Vol. 9
Open Access | Times Cited: 20
Exploring spatio-temporal variation in soundscape saturation of an African tropical forest landscape
Joeri A. Zwerts, J. Wiegers, Elisabeth H. M. Sterck, et al.
Ecological Indicators (2022) Vol. 137, pp. 108712-108712
Open Access | Times Cited: 15
A framework for quantifying soundscape diversity using Hill numbers
Thomas Luypaert, Anderson S. Bueno, Gabriel S. Masseli, et al.
Methods in Ecology and Evolution (2022) Vol. 13, Iss. 10, pp. 2262-2274
Open Access | Times Cited: 15
Towards the development of a citizens’ science-based acoustic rainfall sensing system
Mohammed I. I. Alkhatib, Amin Talei, Tak Kwin Chang, et al.
Journal of Hydrology (2024) Vol. 633, pp. 130973-130973
Open Access | Times Cited: 2
Soundscape segregation based on visual analysis and discriminating features
Fábio Felix Dias, Hélio Pedrini, Rosane Minghim
Ecological Informatics (2020) Vol. 61, pp. 101184-101184
Open Access | Times Cited: 18
A classification and quantification approach to generate features in soundscape ecology using neural networks
Fábio Felix Dias, Moacir Antonelli Ponti, Rosane Minghim
Neural Computing and Applications (2021) Vol. 34, Iss. 3, pp. 1923-1937
Closed Access | Times Cited: 14
Surveillance audio-based rainfall observation: An enhanced strategy for extreme rainfall observation
Xing Wang, Thomas Glade, Elmar Schmaltz, et al.
Applied Acoustics (2023) Vol. 211, pp. 109581-109581
Closed Access | Times Cited: 5
An Urban Acoustic Rainfall Estimation Technique Using a CNN Inversion Approach for Potential Smart City Applications
Mohammed I. I. Alkhatib, Amin Talei, Tak Kwin Chang, et al.
Smart Cities (2023) Vol. 6, Iss. 6, pp. 3112-3137
Open Access | Times Cited: 4
Optimal compactness of fractional Fourier domain characterizes frequency modulated signals
Juan Ugarte, Alejandro Gómez-Echavarría, Catalina Tobón
Chaos Solitons & Fractals (2023) Vol. 177, pp. 114291-114291
Closed Access | Times Cited: 3
An automated multispecies bioacoustics sound classification method based on a nonlinear pattern: Twine-pat
Erhan Akbal, Şengül Doğan, Türker Tuncer
Ecological Informatics (2021) Vol. 68, pp. 101529-101529
Closed Access | Times Cited: 8
CicadaNet: Deep learning based automatic cicada chorus filtering for improved long-term bird monitoring
Chengyun Zhang, Nengting Jin, Jie Xie, et al.
Ecological Indicators (2023) Vol. 158, pp. 111423-111423
Open Access | Times Cited: 2
Automatic bird sound detection: logistic regression based acoustic occupancy model
Yi-Chin Tseng, Bianca N.I. Eskelson, Kathy Martin, et al.
Bioacoustics (2020) Vol. 30, Iss. 3, pp. 324-340
Closed Access | Times Cited: 5
AcoustiCloud: A cloud-based system for managing large-scale bioacoustics processing
Alexander Brown, Saurabh Garg, James Montgomery
Environmental Modelling & Software (2020) Vol. 131, pp. 104778-104778
Closed Access | Times Cited: 5
Estimating rainfall intensity based on surveillance audio and deep-learning
Meizhen Wang, Mingzheng Chen, Ziran Wang, et al.
Environmental Science and Ecotechnology (2024) Vol. 22, pp. 100450-100450
Open Access
The efficacy of acoustic indices for monitoring abundance and diversity in soil soundscapes
Oliver C. Metcalf, Catarina S. Nunes, Carlos Abrahams, et al.
Ecological Indicators (2024) Vol. 169, pp. 112954-112954
Open Access
Software-dependent biases in the recognition of di- and tri-syllabic bird songs can create false interpretations of bird abundance and singing activity
Madalen Goitia-Urdiain, Teresa Sauras‐Yera, Gustavo A. Llorente, et al.
Ecological Informatics (2023) Vol. 79, pp. 102397-102397
Open Access | Times Cited: 1
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