Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

The Flora Incognita app – Interactive plant species identification
Patrick Mäder, David Boho, Michael Rzanny, et al.
Methods in Ecology and Evolution (2021) Vol. 12, Iss. 7, pp. 1335-1342
Open Access | Times Cited: 82

Showing 26-50 of 82 citing articles:

Macrophenological dynamics from citizen science plant occurrence data
Karin Mora, Michael Rzanny, Jana Wäldchen, et al.
Methods in Ecology and Evolution (2024) Vol. 15, Iss. 8, pp. 1422-1437
Open Access | Times Cited: 4
Inconspicuous taxa in citizen science-based botanical research: actual contribution, limitations, and new opportunities for non-vascular cryptogams
Carlos Cerrejón, Marion Noualhaguet, Nicole J. Fenton, et al.
Frontiers in Environmental Science (2025) Vol. 12
Open Access
Making sense of fossils and artefacts: a review of best practices for the design of a successful workflow for machine learning-assisted citizen science projects
Isaak Eijkelboom, Anne S. Schulp, Luc Amkreutz, et al.
PeerJ (2025) Vol. 13, pp. e18927-e18927
Open Access
FlorID – a nationwide identification service for plants from photos and habitat information
Philipp Brun, Lucienne de Witte, Manuel Richard Popp, et al.
Environmental Modelling & Software (2025), pp. 106402-106402
Closed Access
Digital technologies commercially available in Germany in the context of nature conservation and ecosystem service provisioning in agriculture
Tsvetelina Krachunova, Frauke Geppert, Nahleen Lemke, et al.
Frontiers in Sustainable Food Systems (2025) Vol. 9
Open Access
Land‐use affects pollinator‐specific resource availability and pollinator foraging behaviour
Markus Birkenbach, Florian Straub, Anna Kiesel, et al.
Ecology and Evolution (2024) Vol. 14, Iss. 3
Open Access | Times Cited: 3
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: 26
Image-Based Automated Recognition of 31 Poaceae Species: The Most Relevant Perspectives
Michael Rzanny, Hans Christian Wittich, Patrick Mäder, et al.
Frontiers in Plant Science (2022) Vol. 12
Open Access | Times Cited: 17
A machine learning approach for cross-domain plant identification using herbarium specimens
Sophia Chulif, Sue Han Lee, Yang Chang, et al.
Neural Computing and Applications (2022) Vol. 35, Iss. 8, pp. 5963-5985
Open Access | Times Cited: 16
A call to action for inventory and monitoring of cliff ecosystems to support conservation
Georgia R. Harrison, Laura M. Boggess, Sarah E. McCord, et al.
Basic and Applied Ecology (2024) Vol. 80, pp. 31-39
Open Access | Times Cited: 3
Deep models for multi-view 3D object recognition: a review
Mona Alzahrani, Muhammad Usman, Salma Kammoun Jarraya, et al.
Artificial Intelligence Review (2024) Vol. 57, Iss. 12
Open Access | Times Cited: 3
The role of citizen science mobile apps in facilitating a contemporary digital agora
Gheorghe-Gavrilă Hognogi, Mónika Meltzer, Filip Alexandrescu, et al.
Humanities and Social Sciences Communications (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 8
Urban wild bees benefit from flower-rich anthropogenic land use depending on bee trait and scale
Monika Waldis Weber, Tim Diekötter, Anke C. Dietzsch, et al.
Landscape Ecology (2023) Vol. 38, Iss. 11, pp. 2981-2999
Open Access | Times Cited: 7
Challenges and opportunities in applying AI to evolutionary morphology
Yichen He, James M. Mulqueeney, Emily Watt, et al.
(2024)
Open Access | Times Cited: 2
Targeted and untargeted screening of a plant extract library established from raw materials originating from Upper Austria
Bernhard Blank‐Landeshammer, Bettina Schwarzinger, Verena Arnaut, et al.
Food Chemistry (2024) Vol. 451, pp. 139419-139419
Open Access | Times Cited: 2
From simple labels to semantic image segmentation: leveraging citizen science plant photographs for tree species mapping in drone imagery
Salim Soltani, Olga Ferlian, Nico Eisenhauer, et al.
Biogeosciences (2024) Vol. 21, Iss. 11, pp. 2909-2935
Open Access | Times Cited: 2
Eco-evolutionary processes shaping floral nectar sugar composition
Yicong Liu, Susanne Dunker, Walter Durka, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 2
Stable pollinator communities in different white clover populations suggest potential win-win scenarios for crop yield and biodiversity
Marco Ferrante, Felix Kirsch, Catrin Westphal
Agriculture Ecosystems & Environment (2024) Vol. 378, pp. 109295-109295
Open Access | Times Cited: 2
More than rapid identification—Free plant identification apps can also be highly accurate
Michael Rzanny, Anke Bebber, Hans Christian Wittich, et al.
People and Nature (2024)
Open Access | Times Cited: 2
SmartPIV: flow velocity estimates by smartphones for education and field studies
Christian Cierpka, Henning Otto, Constanze Poll, et al.
Experiments in Fluids (2021) Vol. 62, Iss. 8
Open Access | Times Cited: 16
LUCAS cover photos 2006–2018 over the EU: 874 646 spatially distributed geo-tagged close-up photos with land cover and plant species label
Raphaël d’Andrimont, Momchil Yordanov, Laura Martinez-Sanchez, et al.
Earth system science data (2022) Vol. 14, Iss. 10, pp. 4463-4472
Open Access | Times Cited: 9
Methodological challenges and new perspectives of shifting vegetation phenology in eddy covariance data
Annu Panwar, Mirco Migliavacca, Jacob A. Nelson, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 5
Identification of morphologically cryptic species with computer vision models: wall lizards (Squamata: Lacertidae: Podarcis) as a case study
Catarina Pinho, Antigoni Kaliontzopoulou, Carlos Abreu Ferreira, et al.
Zoological Journal of the Linnean Society (2022) Vol. 198, Iss. 1, pp. 184-201
Closed Access | Times Cited: 8
Micro-CT and deep learning: Modern techniques and applications in insect morphology and neuroscience
Thorin Jonsson
Frontiers in Insect Science (2023) Vol. 3
Open Access | Times Cited: 4
A Case Study toward Apple Cultivar Classification Using Deep Learning
Silvia Krug, Tino Hutschenreuther
AgriEngineering (2023) Vol. 5, Iss. 2, pp. 814-828
Open Access | Times Cited: 4

Scroll to top