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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:

Species‐level image classification with convolutional neural network enables insect identification from habitus images
Oskar Liset Pryds Hansen, Jens‐Christian Svenning, Kent Olsen, et al.
Ecology and Evolution (2019) Vol. 10, Iss. 2, pp. 737-747
Open Access | Times Cited: 99

Showing 26-50 of 99 citing articles:

Is it enough to optimize CNN architectures on ImageNet?
Lukas Tuggener, Jürgen Schmidhuber, Thilo Stadelmann
Frontiers in Computer Science (2022) Vol. 4
Open Access | Times Cited: 18
Untargeted Metabolomics for Integrative Taxonomy: Metabolomics, DNA Marker-Based Sequencing, and Phenotype Bioimaging
Kristian Peters, Kaitlyn Blatt-Janmaat, Natalia Tkach, et al.
Plants (2023) Vol. 12, Iss. 4, pp. 881-881
Open Access | Times Cited: 10
Getting the bugs out of AI: Advancing ecological research on arthropods through computer vision
Stefan Schneider, Graham W. Taylor, Stefan C. Kremer, et al.
Ecology Letters (2023) Vol. 26, Iss. 7, pp. 1247-1258
Open Access | Times Cited: 9
Orchard monitoring based on unmanned aerial vehicles and image processing by artificial neural networks: a systematic review
Dan Popescu, Loretta Ichim, Florin Stoican
Frontiers in Plant Science (2023) Vol. 14
Open Access | Times Cited: 9
Bugs and Bytes: Entomological Biomonitoring in the Age of Deep Learning and Beyond
Mukilan Deivarajan Suresh, Tong Xin, Darren M. Evans, et al.
(2024)
Open Access | Times Cited: 3
Detecting and counting sorghum aphid alates using smart computer vision models
Ivan Grijalva, Haley Adams, N. A. Clark, et al.
Ecological Informatics (2024) Vol. 80, pp. 102540-102540
Open Access | Times Cited: 3
A deep learning pipeline for time-lapse camera monitoring of floral environments and insect populations
Kim Bjerge, Henrik Karstoft, Hjalte M. R. Mann, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 3
Towards Machine Vision for Insect Welfare Monitoring and Behavioural Insights
Mark Hansen, A. M. Oparaeke, Ryan Gallagher, et al.
Frontiers in Veterinary Science (2022) Vol. 9
Open Access | Times Cited: 15
Accurate image-based identification of macroinvertebrate specimens using deep learning—How much training data is needed?
Toke T. Høye, Mads Dyrmann, Christian Kjær, et al.
PeerJ (2022) Vol. 10, pp. e13837-e13837
Open Access | Times Cited: 15
Recognizability bias in citizen science photographs
Wouter Koch, Laurens Hogeweg, Erlend B. Nilsen, et al.
Royal Society Open Science (2023) Vol. 10, Iss. 2
Open Access | Times Cited: 8
Photonic sensors reflect variation in insect abundance and diversity across habitats
Klas Rydhmer, Samuel Jansson, Laurence Still, et al.
Ecological Indicators (2023) Vol. 158, pp. 111483-111483
Open Access | Times Cited: 8
Identification of Indian butterflies using Deep Convolutional Neural Network
Hari Theivaprakasham
Journal of Asia-Pacific Entomology (2020) Vol. 24, Iss. 1, pp. 329-340
Closed Access | Times Cited: 21
Using a two-stage convolutional neural network to rapidly identify tiny herbivorous beetles in the field
Hironori Takimoto, Yasuhiro Sato, Atsushi J. Nagano, et al.
Ecological Informatics (2021) Vol. 66, pp. 101466-101466
Open Access | Times Cited: 20
Machine learning for expert‐level image‐based identification of very similar species in the hyperdiverse plant bug family Miridae (Hemiptera: Heteroptera)
Alexander A. Popkov, Fedor V. Konstantinov, В. В. Нейморовец, et al.
Systematic Entomology (2022) Vol. 47, Iss. 3, pp. 487-503
Closed Access | Times Cited: 13
Challenges and opportunities in applying AI to evolutionary morphology
Yichen He, James M. Mulqueeney, Emily Watt, et al.
(2024)
Open Access | Times Cited: 2
Inferring Taxonomic Affinities and Genetic Distances Using Morphological Features Extracted from Specimen Images: a Case Study with a Bivalve dataset
Martin Hofmann, Steffen Kiel, Lara M. Kösters, et al.
Systematic Biology (2024)
Closed Access | Times Cited: 2
Deep learning image analysis for filamentous fungi taxonomic classification: Dealing with small data sets with class imbalance and hierarchical grouping
Stefan Stiller, Juan F. Dueñas, Stefan Hempel, et al.
Biology Methods and Protocols (2024) Vol. 9, Iss. 1
Open Access | Times Cited: 2
An Efficient Pest Detection Framework with a Medium-Scale Benchmark to Increase the Agricultural Productivity
Suliman Aladhadh, Shabana Habib, Muhammad Islam, et al.
Sensors (2022) Vol. 22, Iss. 24, pp. 9749-9749
Open Access | Times Cited: 10
Pretrained Convolutional Neural Networks Perform Well in a Challenging Test Case: Identification of Plant Bugs (Hemiptera: Miridae) Using a Small Number of Training Images
Alexander Knyshov, Samantha Hoang, Christiane Weirauch
Insect Systematics and Diversity (2021) Vol. 5, Iss. 2
Closed Access | Times Cited: 13
Deep learning approach to classify Tiger beetles of Sri Lanka
Lakmini Abeywardhana, C. D. Dangalle, Anupiya Nugaliyadde, et al.
Ecological Informatics (2021) Vol. 62, pp. 101286-101286
Closed Access | Times Cited: 13
Insect Image Semantic Segmentation and Identification Using UNET and DeepLab V3+
Kunal Bose, Kumar Shubham, Vivek Tiwari, et al.
Lecture notes in networks and systems (2022), pp. 703-711
Closed Access | Times Cited: 9
Wing Interferential Patterns (WIPs) and machine learning for the classification of some Aedes species of medical interest
Arnaud Cannet, Camille Simon-Chane, Aymeric Histace, 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
‘Citizen identification’: online learning supports highly accurate species identification for insect‐focussed citizen science
Jessica Perry, Seirian Sumner, Cris Thompson, et al.
Insect Conservation and Diversity (2021) Vol. 14, Iss. 6, pp. 862-867
Open Access | Times Cited: 11
Leveraging Hyperspectral Images for Accurate Insect Classification with a Novel Two-Branch Self-Correlation Approach
Siqiao Tan, Shuzhen Hu, Shaofang He, et al.
Agronomy (2024) Vol. 14, Iss. 4, pp. 863-863
Open Access | Times Cited: 1

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