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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:

Thinking like a naturalist: Enhancing computer vision of citizen science images by harnessing contextual data
J. Christopher D. Terry, Helen E. Roy, Tom August
Methods in Ecology and Evolution (2019) Vol. 11, Iss. 2, pp. 303-315
Open Access | Times Cited: 75

Showing 1-25 of 75 citing articles:

Scientists' warning on invasive alien species
Petr Pyšek, Philip E. Hulme, Daniel Simberloff, et al.
Biological reviews/Biological reviews of the Cambridge Philosophical Society (2020) Vol. 95, Iss. 6, pp. 1511-1534
Open Access | Times Cited: 1598
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: 162
Outstanding challenges and future directions for biodiversity monitoring using citizen science data
Alison Johnston, Eleni Matechou, Emily B. Dennis
Methods in Ecology and Evolution (2022) Vol. 14, Iss. 1, pp. 103-116
Open Access | Times Cited: 138
Power of the people: A review of citizen science programs for conservation
Victoria J. MacPhail, Sheila R. Colla
Biological Conservation (2020) Vol. 249, pp. 108739-108739
Open Access | Times Cited: 100
Human-machine-learning integration and task allocation in citizen science
Marisa Ponti, Alena Seredko
Humanities and Social Sciences Communications (2022) Vol. 9, Iss. 1
Open Access | Times Cited: 56
A review of invasive species reporting apps for citizen science and opportunities for innovation
Leif Howard, Charles B. van Rees, Zoe Dahlquist, et al.
NeoBiota (2022) Vol. 71, pp. 165-188
Open Access | Times Cited: 50
Family as a Third Space for AI Literacies: How do children and parents learn about AI together?
Stefania Druga, Fee Lia Christoph, Amy J. Ko
CHI Conference on Human Factors in Computing Systems (2022), pp. 1-17
Open Access | Times Cited: 42
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 | Times Cited: 1
Improving the accessibility and transferability of machine learning algorithms for identification of animals in camera trap images: MLWIC2
Michael A. Tabak, Mohammad Sadegh Norouzzadeh, David W. Wolfson, et al.
Ecology and Evolution (2020) Vol. 10, Iss. 19, pp. 10374-10383
Open Access | Times Cited: 61
The Partnership of Citizen Science and Machine Learning: Benefits, Risks, and Future Challenges for Engagement, Data Collection, and Data Quality
Maryam Lotfian, Jens Ingensand, Maria Antonia Brovelli
Sustainability (2021) Vol. 13, Iss. 14, pp. 8087-8087
Open Access | Times Cited: 51
Classifying the content of social media images to support cultural ecosystem service assessments using deep learning models
Ana Sofia Cardoso, Francesco Renna, Ricardo Moreno-Llorca, et al.
Ecosystem Services (2022) Vol. 54, pp. 101410-101410
Closed Access | Times Cited: 32
Dynamic MLP for Fine-Grained Image Classification by Leveraging Geographical and Temporal Information
Lingfeng Yang, Xiang Li, Renjie Song, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2022)
Open Access | Times Cited: 32
A gentle introduction to computer vision‐based specimen classification in ecological datasets
Jarrett Blair, Kaitlyn M. Gaynor, Meredith S. Palmer, et al.
Journal of Animal Ecology (2024) Vol. 93, Iss. 2, pp. 147-158
Open Access | Times Cited: 8
The Role of Community Science in Entomology
Mary M. Gardiner, Helen E. Roy
Annual Review of Entomology (2021) Vol. 67, Iss. 1, pp. 437-456
Open Access | Times Cited: 35
Crowd‐sourced plant occurrence data provide a reliable description of macroecological gradients
Miguel D. Mahecha, Michael Rzanny, Guido Kraemer, et al.
Ecography (2021) Vol. 44, Iss. 8, pp. 1131-1142
Open Access | Times Cited: 34
Citizen Science and Monitoring Forest Pests: a Beneficial Alliance?
Maarten de Groot, Michael J. O. Pocock, Jochem Bonte, et al.
Current Forestry Reports (2022) Vol. 9, Iss. 1, pp. 15-32
Open Access | Times Cited: 27
Few‐shot learning for plant disease recognition: A review
Jianqiang Sun, Wei Cao, Fu Xi, et al.
Agronomy Journal (2023) Vol. 116, Iss. 3, pp. 1204-1216
Open Access | Times Cited: 16
Improving deep learning acoustic classifiers with contextual information for wildlife monitoring
Lorène Jeantet, Emmanuel Dufourq
Ecological Informatics (2023) Vol. 77, pp. 102256-102256
Open Access | Times Cited: 14
Exploring the landscape of automated species identification apps: Development, promise, and user appraisal
Minh-Xuân Truong, René van der Wal
BioScience (2024) Vol. 74, Iss. 9, pp. 601-613
Open Access | Times Cited: 6
Improved Wildlife Recognition through Fusing Camera Trap Images and Temporal Metadata
Lei Liu, Chao Mou, Fu Xu
Diversity (2024) Vol. 16, Iss. 3, pp. 139-139
Open Access | Times Cited: 5
Towards robust classification of multi-view remote sensing images with partial data availability
Maofan Zhao, Qingyan Meng, Lifeng Wang, et al.
Remote Sensing of Environment (2024) Vol. 306, pp. 114112-114112
Closed Access | Times Cited: 5
Flora Capture: a citizen science application for collecting structured plant observations
David Boho, Michael Rzanny, Jana Wäldchen, et al.
BMC Bioinformatics (2020) Vol. 21, Iss. 1
Open Access | Times Cited: 35
Revisiting animal photo‐identification using deep metric learning and network analysis
Vincent Miele, Gaspard Dussert, B. Spataro, et al.
Methods in Ecology and Evolution (2021) Vol. 12, Iss. 5, pp. 863-873
Open Access | Times Cited: 32
Plant image identification application demonstrates high accuracy in Northern Europe
Jaak Pärtel, Meelis Pärtel, Jana Wäldchen
AoB Plants (2021) Vol. 13, Iss. 4
Open Access | Times Cited: 27
Assessing deep convolutional neural network models and their comparative performance for automated medicinal plant identification from leaf images
Biplob Dey, Jannatul Ferdous, Romel Ahmed, et al.
Heliyon (2023) Vol. 10, Iss. 1, pp. e23655-e23655
Open Access | Times Cited: 11
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