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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:

High Throughput Data Acquisition and Deep Learning for Insect Ecoinformatics
Alexander Gerovichev, Achiad Sadeh, Vlad Winter, et al.
Frontiers in Ecology and Evolution (2021) Vol. 9
Open Access | Times Cited: 32

Showing 1-25 of 32 citing articles:

Emerging technologies revolutionise insect ecology and monitoring
Roel van Klink, Tom August, Yves Bas, et al.
Trends in Ecology & Evolution (2022) Vol. 37, Iss. 10, pp. 872-885
Open Access | Times Cited: 177
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
Detection of Soybean Insect Pest and a Forecasting Platform Using Deep Learning with Unmanned Ground Vehicles
Yu-Hyeon Park, Sung Hoon Choi, Yeon-Ju Kwon, et al.
Agronomy (2023) Vol. 13, Iss. 2, pp. 477-477
Open Access | Times Cited: 28
An intelligent system for high-density small target pest identification and infestation level determination based on an improved YOLOv5 model
Li Sun, Zhenghua Cai, Kaibo Liang, et al.
Expert Systems with Applications (2023) Vol. 239, pp. 122190-122190
Closed Access | Times Cited: 17
Artificial neuronal networks are revolutionizing entomological research
Manfred Hartbauer
Journal of Applied Entomology (2024) Vol. 148, Iss. 2, pp. 232-251
Open Access | Times Cited: 7
Object Detection of Small Insects in Time-Lapse Camera Recordings
Kim Bjerge, Carsten Eie Frigaard, Henrik Karstoft
Sensors (2023) Vol. 23, Iss. 16, pp. 7242-7242
Open Access | Times Cited: 15
Classification of Fruit Flies by Gender in Images Using Smartphones and the YOLOv4-Tiny Neural Network
М. А. Генаев, Е. Г. Комышев, Olga D. Shishkina, et al.
Mathematics (2022) Vol. 10, Iss. 3, pp. 295-295
Open Access | Times Cited: 19
Evaluating the method reproducibility of deep learning models in biodiversity research
Waqas Ahmed, Vamsi Krishna Kommineni, Birgitta König‐Ries, et al.
PeerJ Computer Science (2025) Vol. 11, pp. e2618-e2618
Open Access
Machine learning for automated electrical penetration graph analysis of aphid feeding behavior: Accelerating research on insect-plant interactions
Quang Dung Dinh, Daniel Kunk, Truong Son Hy, et al.
PLoS ONE (2025) Vol. 20, Iss. 4, pp. e0319484-e0319484
Open Access
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
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
STARdbi: A pipeline and database for insect monitoring based on automated image analysis
Tamar Keasar, Michael Yair, Daphna Gottlieb, et al.
Ecological Informatics (2024) Vol. 80, pp. 102521-102521
Open Access | Times Cited: 3
SRNet-YOLO: A model for detecting tiny and very tiny pests in cotton fields based on super-resolution reconstruction
Sen Yang, Gang Zhou, Yuwei Feng, et al.
Frontiers in Plant Science (2024) Vol. 15
Open Access | Times Cited: 3
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
BOVIDS: A deep learning‐based software package for pose estimation to evaluate nightly behavior and its application to common elands (Tragelaphus oryx) in zoos
Jennifer Gübert, Max Hahn‐Klimroth, Paul Wilhelm Dierkes
Ecology and Evolution (2022) Vol. 12, Iss. 3
Open Access | Times Cited: 10
Insect Detection in Sticky Trap Images of Tomato Crops Using Machine Learning
Tiago Domingues, Tomás Brandão, Ricardo Ribeiro, et al.
Agriculture (2022) Vol. 12, Iss. 11, pp. 1967-1967
Open Access | Times Cited: 10
Low Cost Machine Vision for Insect Classification
Danja Brandt, Martin Tschaikner, Teodor Chiaburu, et al.
Lecture notes in networks and systems (2024), pp. 18-34
Closed Access | Times Cited: 1
Bugs and bytes: Entomological biomonitoring through the integration of deep learning and molecular analysis for merged community and network analysis
Mukilan Deivarajan Suresh, Tong Xin, S. M. Cook, et al.
Agricultural and Forest Entomology (2024)
Open Access | Times Cited: 1
Suivis de biodiversité par la reconnaissance automatique des espèces sur photographies : perspectives et défis
H. Le Borgne, Christophe Bouget
Naturae (2023), Iss. 6
Open Access | Times Cited: 3
Classification of Soybean [Glycine max (L.) Merr.] Seed Based on Deep Learning Using the YOLOv5 Model
Yu-Hyeon Park, Tae‐Hwan Jun
Plant Breeding and Biotechnology (2022) Vol. 10, Iss. 1, pp. 75-80
Closed Access | Times Cited: 5
Machine learning for characterizing plant-insect interactions through electrical penetration graphic signal
Quang Dung Dinh, Daniel Kunk, Truong Son Hy, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Intelligent pest trap monitoring under uncertainty in food industry
Suling Duan, Yong Li, Bin Zhu, et al.
Swarm and Evolutionary Computation (2023) Vol. 86, pp. 101465-101465
Closed Access | Times Cited: 1
Getting the Bugs Out: Entomology Using Computer Vision
Stefan Schneider, Graham Taylor, Stefan C. Kremer, et al.
Authorea (Authorea) (2022)
Open Access | Times Cited: 2
Accurate detection and identification of insects from camera trap images with deep learning
Kim Bjerge, Jamie Alison, Mads Dyrmann, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 1
InsectEye: An Intelligent Trap for Insect Biodiversity Monitoring
Eric Homan, Codey Mathis, Chonghan Lee, et al.
(2023), pp. 1-6
Closed Access
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