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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:

Behaviour classification of extensively grazed sheep using machine learning
Eloise S. Fogarty, David L. Swain, G. M. Cronin, et al.
Computers and Electronics in Agriculture (2019) Vol. 169, pp. 105175-105175
Closed Access | Times Cited: 97

Showing 1-25 of 97 citing articles:

Machine Learning in Agriculture: A Comprehensive Updated Review
Lefteris Benos, Aristotelis C. Tagarakis, Georgios Dolias, et al.
Sensors (2021) Vol. 21, Iss. 11, pp. 3758-3758
Open Access | Times Cited: 526
A systematic literature review on the use of machine learning in precision livestock farming
Rodrigo García, José Aguilar, Mauricio Toro, et al.
Computers and Electronics in Agriculture (2020) Vol. 179, pp. 105826-105826
Open Access | Times Cited: 206
Predicting livestock behaviour using accelerometers: A systematic review of processing techniques for ruminant behaviour prediction from raw accelerometer data
Lucile Riaboff, L. Shalloo, Alan F. Smeaton, et al.
Computers and Electronics in Agriculture (2021) Vol. 192, pp. 106610-106610
Open Access | Times Cited: 131
Computer-vision classification of corn seed varieties using deep convolutional neural network
Shima Javanmardi, Seyed-Hassan Miraei Ashtiani, Fons J. Verbeek, et al.
Journal of Stored Products Research (2021) Vol. 92, pp. 101800-101800
Open Access | Times Cited: 123
Deep learning-based animal activity recognition with wearable sensors: Overview, challenges, and future directions
Axiu Mao, Endai Huang, Xiaoshuai Wang, et al.
Computers and Electronics in Agriculture (2023) Vol. 211, pp. 108043-108043
Closed Access | Times Cited: 46
Livestock Management With Unmanned Aerial Vehicles: A Review
Mohammed Ateeq Alanezi, Mohammad Shoaib Shahriar, Md. Bakhtiar Hasan, et al.
IEEE Access (2022) Vol. 10, pp. 45001-45028
Open Access | Times Cited: 62
Deep transfer learning in sheep activity recognition using accelerometer data
Natasa Kleanthous, Abir Hussain, Wasiq Khan, et al.
Expert Systems with Applications (2022) Vol. 207, pp. 117925-117925
Open Access | Times Cited: 48
Application of deep learning in sheep behaviors recognition and influence analysis of training data characteristics on the recognition effect
Man Cheng, Hongbo Yuan, Qifan Wang, et al.
Computers and Electronics in Agriculture (2022) Vol. 198, pp. 107010-107010
Closed Access | Times Cited: 46
A survey of machine learning approaches in animal behaviour
Natasa Kleanthous, Abir Hussain, Wasiq Khan, et al.
Neurocomputing (2022) Vol. 491, pp. 442-463
Open Access | Times Cited: 39
ActBeCalf: Accelerometer-Based Multivariate Time-Series Dataset for Calf Behavior Classification
Oshana Dissanayake, Sarah E. McPherson, Joseph Allyndrée, et al.
Data in Brief (2025), pp. 111462-111462
Open Access | Times Cited: 1
Can accelerometer ear tags identify behavioural changes in sheep associated with parturition?
Eloise S. Fogarty, David L. Swain, G. M. Cronin, et al.
Animal Reproduction Science (2020) Vol. 216, pp. 106345-106345
Closed Access | Times Cited: 54
Behavior classification and spatiotemporal analysis of grazing sheep using deep learning
Zhongming Jin, Hang Shu, Tianci Hu, et al.
Computers and Electronics in Agriculture (2024) Vol. 220, pp. 108894-108894
Closed Access | Times Cited: 8
Developing a Simulated Online Model That Integrates GNSS, Accelerometer and Weather Data to Detect Parturition Events in Grazing Sheep: A Machine Learning Approach
Eloise S. Fogarty, David L. Swain, G. M. Cronin, et al.
Animals (2021) Vol. 11, Iss. 2, pp. 303-303
Open Access | Times Cited: 35
Deep learning based classification of sheep behaviour from accelerometer data with imbalance
Kirk E. Turner, A. N. Thompson, Ian Harris, et al.
Information Processing in Agriculture (2022) Vol. 10, Iss. 3, pp. 377-390
Open Access | Times Cited: 23
Livestock feeding behaviour: A review on automated systems for ruminant monitoring
José O. Chelotti, Luciano S. Martinez-Rau, Mariano Ferrero, et al.
Biosystems Engineering (2024) Vol. 246, pp. 150-177
Open Access | Times Cited: 6
Identifying animal behaviours from accelerometers: Improving predictive accuracy of machine learning by refining the variables selected, data frequency, and sample duration
Carolyn E. Dunford, Nikki J. Marks, Rory P. Wilson, et al.
Ecology and Evolution (2024) Vol. 14, Iss. 5
Open Access | Times Cited: 5
Motion focus global–local network: Combining attention mechanism with micro action features for cow behavior recognition
Hongbo Geng, Zhenjie Hou, Jiuzhen Liang, et al.
Computers and Electronics in Agriculture (2024) Vol. 226, pp. 109399-109399
Closed Access | Times Cited: 5
Development of micro-level classifiers from land suitability analysis for drought-prone areas in Indonesia
Muhammad Iqbal Habibie, Ryozo Noguchi, Shusuke Matsushita, et al.
Remote Sensing Applications Society and Environment (2020) Vol. 20, pp. 100421-100421
Closed Access | Times Cited: 33
Classifying the posture and activity of ewes and lambs using accelerometers and machine learning on a commercial flock
Emily Price, Joss Langford, Tim W. Fawcett, et al.
Applied Animal Behaviour Science (2022) Vol. 251, pp. 105630-105630
Closed Access | Times Cited: 22
Behavioral Fingerprinting: Acceleration Sensors for Identifying Changes in Livestock Health
Bowen Fan, Racheal H. Bryant, Andrew W. Greer
J — Multidisciplinary Scientific Journal (2022) Vol. 5, Iss. 4, pp. 435-454
Open Access | Times Cited: 21
Real-Time Monitoring of Grazing Cattle Using LORA-WAN Sensors to Improve Precision in Detecting Animal Welfare Implications via Daily Distance Walked Metrics
Shelemia Nyamuryekung’e, Glenn C Duff, Santiago A. Utsumi, et al.
Animals (2023) Vol. 13, Iss. 16, pp. 2641-2641
Open Access | Times Cited: 12
Detection of rumination in cattle using an accelerometer ear-tag: A comparison of analytical methods and individual animal and generic models
Anita Z. Chang, Eloise S. Fogarty, L.E. Moraes, et al.
Computers and Electronics in Agriculture (2021) Vol. 192, pp. 106595-106595
Open Access | Times Cited: 26
Multimodal sensor data fusion for in-situ classification of animal behavior using accelerometry and GNSS data
Reza Arablouei, Ziwei Wang, Greg Bishop-Hurley, et al.
Smart Agricultural Technology (2022) Vol. 4, pp. 100163-100163
Open Access | Times Cited: 19
Recognition of Cattle's Feeding Behaviors Using Noseband Pressure Sensor With Machine Learning
Guipeng Chen, Cong Li, Yang Guo, et al.
Frontiers in Veterinary Science (2022) Vol. 9
Open Access | Times Cited: 17
A full end-to-end deep approach for detecting and classifying jaw movements from acoustic signals in grazing cattle
Mariano Ferrero, Leandro D. Vignolo, Sebastián R. Vanrell, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 121, pp. 106016-106016
Closed Access | Times Cited: 11
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