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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:

Applications for deep learning in ecology
Sylvain Christin, Éric Hervet, Nicolas Lecomte
Methods in Ecology and Evolution (2019) Vol. 10, Iss. 10, pp. 1632-1644
Open Access | Times Cited: 523

Showing 1-25 of 523 citing articles:

SLEAP: A deep learning system for multi-animal pose tracking
Talmo Pereira, Nathaniel Tabris, Arie Matsliah, et al.
Nature Methods (2022) Vol. 19, Iss. 4, pp. 486-495
Open Access | Times Cited: 458
Perspectives in machine learning for wildlife conservation
Devis Tuia, Benjamin Kellenberger, Sara Beery, et al.
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 407
Deep learning and computer vision will transform entomology
Toke T. Høye, Johanna Ärje, Kim Bjerge, et al.
Proceedings of the National Academy of Sciences (2021) Vol. 118, Iss. 2
Open Access | Times Cited: 333
AlphaFold2 and its applications in the fields of biology and medicine
Zhenyu Yang, Xiaoxi Zeng, Yi Zhao, et al.
Signal Transduction and Targeted Therapy (2023) Vol. 8, Iss. 1
Open Access | Times Cited: 267
Quantifying behavior to understand the brain
Talmo Pereira, Joshua W. Shaevitz, Mala Murthy
Nature Neuroscience (2020) Vol. 23, Iss. 12, pp. 1537-1549
Open Access | Times Cited: 259
High-resolution mapping of forest canopy height using machine learning by coupling ICESat-2 LiDAR with Sentinel-1, Sentinel-2 and Landsat-8 data
Wang Li, Zheng Niu, Rong Shang, et al.
International Journal of Applied Earth Observation and Geoinformation (2020) Vol. 92, pp. 102163-102163
Open Access | Times Cited: 227
Machine learning and deep learning—A review for ecologists
Maximilian Pichler, Florian Härtig
Methods in Ecology and Evolution (2023) Vol. 14, Iss. 4, pp. 994-1016
Open Access | Times Cited: 200
Improving Landsat predictions of rangeland fractional cover with multitask learning and uncertainty
Brady Allred, Brandon T. Bestelmeyer, Chad S. Boyd, et al.
Methods in Ecology and Evolution (2021) Vol. 12, Iss. 5, pp. 841-849
Open Access | Times Cited: 192
iEcology: Harnessing Large Online Resources to Generate Ecological Insights
Ivan Jarić, Ricardo A. Correia, Barry W. Brook, et al.
Trends in Ecology & Evolution (2020) Vol. 35, Iss. 7, pp. 630-639
Open Access | Times Cited: 184
ForestGEO: Understanding forest diversity and dynamics through a global observatory network
Stuart J. Davies, Iveren Abiem, Kamariah Abu Salim, et al.
Biological Conservation (2020) Vol. 253, pp. 108907-108907
Open Access | Times Cited: 183
A Comprehensive Overview of Technologies for Species and Habitat Monitoring and Conservation
José J. Lahoz‐Monfort, Michael J. L. Magrath
BioScience (2021) Vol. 71, Iss. 10, pp. 1038-1062
Open Access | Times Cited: 172
Deep learning as a tool for ecology and evolution
Marek L. Borowiec, Rebecca B. Dikow, Paul B. Frandsen, et al.
Methods in Ecology and Evolution (2022) Vol. 13, Iss. 8, pp. 1640-1660
Open Access | Times Cited: 164
Towards the fully automated monitoring of ecological communities
Marc Besson, Jamie Alison, Kim Bjerge, et al.
Ecology Letters (2022) Vol. 25, Iss. 12, pp. 2753-2775
Open Access | Times Cited: 157
Deep learning‐based methods for individual recognition in small birds
André C. Ferreira, Liliana R. Silva, Francesco Renna, et al.
Methods in Ecology and Evolution (2020) Vol. 11, Iss. 9, pp. 1072-1085
Open Access | Times Cited: 154
Potential for Artificial Intelligence (AI) and Machine Learning (ML) Applications in Biodiversity Conservation, Managing Forests, and Related Services in India
K. Nagaraju Shivaprakash, Niraj Swami, Sagar Mysorekar, et al.
Sustainability (2022) Vol. 14, Iss. 12, pp. 7154-7154
Open Access | Times Cited: 102
Frontiers in quantifying wildlife behavioural responses to chemical pollution
Michael G. Bertram, Jake M. Martin, Erin S. McCallum, et al.
Biological reviews/Biological reviews of the Cambridge Philosophical Society (2022) Vol. 97, Iss. 4, pp. 1346-1364
Open Access | Times Cited: 99
Artificial intelligence and automated monitoring for assisting conservation of marine ecosystems: A perspective
Ellen M. Ditria, Christina A. Buelow, Manuel González‐Rivero, et al.
Frontiers in Marine Science (2022) Vol. 9
Open Access | Times Cited: 79
Collapse of terrestrial mammal food webs since the Late Pleistocene
Evan C. Fricke, Chia Hsieh, Owen Middleton, et al.
Science (2022) Vol. 377, Iss. 6609, pp. 1008-1011
Closed Access | Times Cited: 79
An evaluation of platforms for processing camera‐trap data using artificial intelligence
Juliana Vélez, William J. McShea, Hila Shamon, et al.
Methods in Ecology and Evolution (2022) Vol. 14, Iss. 2, pp. 459-477
Open Access | Times Cited: 74
Accurate detection and identification of insects from camera trap images with deep learning
Kim Bjerge, Jamie Alison, Mads Dyrmann, et al.
PLOS Sustainability and Transformation (2023) Vol. 2, Iss. 3, pp. e0000051-e0000051
Open Access | Times Cited: 67
Artificial intelligence for geoscience: Progress, challenges and perspectives
Tianjie Zhao, Sheng Wang, Chaojun Ouyang, et al.
The Innovation (2024) Vol. 5, Iss. 5, pp. 100691-100691
Open Access | Times Cited: 61
Machine learning in marine ecology: an overview of techniques and applications
Peter Rubbens, Stephanie Brodie, Tristan Cordier, et al.
ICES Journal of Marine Science (2023) Vol. 80, Iss. 7, pp. 1829-1853
Open Access | Times Cited: 54
A Survey of Intelligent Detection Designs of HTML URL Phishing Attacks
Sultan Asiri, Yang Xiao, Saleh Alzahrani, et al.
IEEE Access (2023) Vol. 11, pp. 6421-6443
Open Access | Times Cited: 50
The importance of genomic variation for biodiversity, ecosystems and people
Madlen Stange, Rowan D. H. Barrett, Andrew P. Hendry
Nature Reviews Genetics (2020) Vol. 22, Iss. 2, pp. 89-105
Closed Access | Times Cited: 133
Effects of sample size and network depth on a deep learning approach to species distribution modeling
Donald J. Benkendorf, Charles P. Hawkins
Ecological Informatics (2020) Vol. 60, pp. 101137-101137
Open Access | Times Cited: 106
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