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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:

FathomNet: A global image database for enabling artificial intelligence in the ocean
Kakani Katija, Eric C. Orenstein, Brian Schlining, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 61

Showing 1-25 of 61 citing articles:

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: 50
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: 40
A synergistic future for AI and ecology
Barbara A. Han, Kush R. Varshney, Shannon L. LaDeau, et al.
Proceedings of the National Academy of Sciences (2023) Vol. 120, Iss. 38
Open Access | Times Cited: 23
Semi-supervised Visual Tracking of Marine Animals Using Autonomous Underwater Vehicles
Levi Cai, Nathan E. McGuire, Roger T. Hanlon, et al.
International Journal of Computer Vision (2023) Vol. 131, Iss. 6, pp. 1406-1427
Open Access | Times Cited: 22
Image dataset for benchmarking automated fish detection and classification algorithms
Marco Francescangeli, Simone Marini, Enoc Martínez Padró, et al.
Scientific Data (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 18
Revolutionizing Marine Traffic Management: A Comprehensive Review of Machine Learning Applications in Complex Maritime Systems
Irmina Durlik, Tymoteusz Miller, Lech Dorobczyński, et al.
Applied Sciences (2023) Vol. 13, Iss. 14, pp. 8099-8099
Open Access | Times Cited: 15
A data-centric framework for combating domain shift in underwater object detection with image enhancement
Lukas Folkman, Kylie A. Pitt, Bela Stantić
Applied Intelligence (2025) Vol. 55, Iss. 4
Open Access
Surveying the deep: A review of computer vision in the benthos
Cameron Trotter, Huw J. Griffiths, Rowan J. Whittle
Ecological Informatics (2025), pp. 102989-102989
Open Access
BenthicNet: A global compilation of seafloor images for deep learning applications
Scott Lowe, Benjamin Misiuk, Isaac Xu, et al.
Scientific Data (2025) Vol. 12, Iss. 1
Open Access
Benthic community heterogeneity on the Eastern Antarctic continental shelf
Candace J. Grimes, Andrew R. Mahon, Kyle Donnelly, et al.
Polar Biology (2025) Vol. 48, Iss. 1
Open Access
A benthic substrate classification method for seabed images using deep learning: Application to management of deep‐sea coral reefs
Chris Jackett, Franziska Althaus, Kylie Maguire, et al.
Journal of Applied Ecology (2023) Vol. 60, Iss. 7, pp. 1254-1273
Open Access | Times Cited: 15
Context-Driven Detection of Invertebrate Species in Deep-Sea Video
R. Austin McEver, Bowen Zhang, Connor Levenson, et al.
International Journal of Computer Vision (2023) Vol. 131, Iss. 6, pp. 1367-1388
Open Access | Times Cited: 14
Exposing inequities in deep-sea exploration and research: results of the 2022 Global Deep-Sea Capacity Assessment
Katherine L.C. Bell, Maud C. Quinzin, Diva J. Amon, et al.
Frontiers in Marine Science (2023) Vol. 10
Open Access | Times Cited: 13
Antarctic benthic ecological change
Huw J. Griffiths, Vonda J. Cummings, Anton Van de Putte, et al.
Nature Reviews Earth & Environment (2024) Vol. 5, Iss. 9, pp. 645-664
Closed Access | Times Cited: 4
An in situ digital synthesis strategy for the discovery and description of ocean life
John A. Burns, Kaitlyn P. Becker, David Casagrande, et al.
Science Advances (2024) Vol. 10, Iss. 3
Open Access | Times Cited: 3
Towards standardizing automated image analysis with artificial intelligence for biodiversity
Peng Zhou, Yu-Xin Bu, Ge‐Yi Fu, et al.
Frontiers in Marine Science (2024) Vol. 11
Open Access | Times Cited: 3
Marine lebensspuren: improving the classification of seafloor traces from underwater imagery and observations
Olmo Miguez‐Salas, Rachel Przeslawski, Francisco J. Rodríguez‐Tovar, et al.
Frontiers in Marine Science (2024) Vol. 11
Open Access | Times Cited: 3
Automated species classification and counting by deep-sea mobile crawler platforms using YOLO
Luciano Ortenzi, Jacopo Aguzzi, Corrado Costa, et al.
Ecological Informatics (2024) Vol. 82, pp. 102788-102788
Open Access | Times Cited: 3
Accelerating ocean species discovery and laying the foundations for the future of marine biodiversity research and monitoring
Alex D. Rogers, Hannah J. Appiah-Madson, Jeff Ardron, et al.
Frontiers in Marine Science (2023) Vol. 10
Open Access | Times Cited: 8
Underwater Mediterranean image analysis based on the compute continuum paradigm
Michele Ferrari, Daniele D’Agostino, Jacopo Aguzzi, et al.
Future Generation Computer Systems (2024) Vol. 162, pp. 107481-107481
Open Access | Times Cited: 2
Demystifying image-based machine learning: a practical guide to automated analysis of field imagery using modern machine learning tools
Byron T. Belcher, Eliana H. Bower, Benjamin P. Burford, et al.
Frontiers in Marine Science (2023) Vol. 10
Open Access | Times Cited: 7
Advanced marine technologies for ocean research
Allison J. Miller, Jyotika I. Virmani
Deep Sea Research Part II Topical Studies in Oceanography (2023) Vol. 212, pp. 105340-105340
Open Access | Times Cited: 7
Convolutional neural networks for hydrothermal vents substratum classification: An introspective study
Pedro Juan Soto Vega, Panagiotis Papadakis, Marjolaine Matabos, et al.
Ecological Informatics (2024) Vol. 80, pp. 102535-102535
Open Access | Times Cited: 2
Cyber Security Challenges and Dark Side of AI
Nitish Kumar Ojha, Archana Pandita, J. Ramkumar
Advances in human resources management and organizational development book series (2024), pp. 117-137
Closed Access | Times Cited: 2
From Coarse to Fine-Grained Open-Set Recognition
Nico Lang, Vésteinn Snæbjarnarson, Elijah Cole, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2024), pp. 17804-17814
Closed Access | Times Cited: 2
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