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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:

Freedom to lie: How farrowing environment affects sow lying behaviour assessment using inertial sensors
Robin Thompson, Stephen G. Matthews, Thomas Plötz, et al.
Computers and Electronics in Agriculture (2019) Vol. 157, pp. 549-557
Closed Access | Times Cited: 21

Showing 21 citing articles:

A Systematic Review on Validated Precision Livestock Farming Technologies for Pig Production and Its Potential to Assess Animal Welfare
Yaneth Gómez, Anna H. Stygar, I.J.M.M. Boumans, et al.
Frontiers in Veterinary Science (2021) Vol. 8
Open Access | Times Cited: 99
Accelerometer systems as tools for health and welfare assessment in cattle and pigs – A review
J.M. Chapa, Kristina Maschat, Michael Iwersen, et al.
Behavioural Processes (2020) Vol. 181, pp. 104262-104262
Open Access | Times Cited: 93
Information Technologies for Welfare Monitoring in Pigs and Their Relation to Welfare Quality®
Mona Lilian Vestbjerg Larsen, Meiqing Wang, Tomás Norton
Sustainability (2021) Vol. 13, Iss. 2, pp. 692-692
Open Access | Times Cited: 59
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
Farmers’ Perspectives of the Benefits and Risks in Precision Livestock Farming in the EU Pig and Poultry Sectors
Idan Kopler, U. Marchaim, Ildikó Edit Tikász, et al.
Animals (2023) Vol. 13, Iss. 18, pp. 2868-2868
Open Access | Times Cited: 23
Transforming the Adaptation Physiology of Farm Animals through Sensors
Suresh Neethirajan
Animals (2020) Vol. 10, Iss. 9, pp. 1512-1512
Open Access | Times Cited: 63
Analysis of pig activity level and body temperature variation based on ear tag data
Yigui Huang, Deqin Xiao, Junbin Liu, et al.
Computers and Electronics in Agriculture (2024) Vol. 219, pp. 108768-108768
Closed Access | Times Cited: 6
Vision Transformers for Automated Detection of Pig Interactions in groups
Gbadegesin Adetayo Taiwo, Sunil Vadera, Ali Alameer
Smart Agricultural Technology (2025), pp. 100774-100774
Open Access
Behavioural complexity in fattening pigs I. Video-based validation of a novel welfare indicator according to varying intensity of housing conditions
Christina Raudies, Maximilian Knoll, Lorenz Gygax
Applied Animal Behaviour Science (2025), pp. 106605-106605
Open Access
A Review in the Automatic Detection of Pigs Behavior with Sensors
Ziting Zhang, Hang Zhang, HE Yu-xiang, et al.
Journal of Sensors (2022) Vol. 2022, pp. 1-17
Open Access | Times Cited: 15
Sow serenity: automatic long-term measurement of lying behavior in crates and free-farrowing pens using 3D accelerometers
Maximilian Knoll, Lorenz Gygax, Edna Hillmann
Journal of Animal Science (2024) Vol. 102
Open Access | Times Cited: 2
Artificial intelligence and porcine breeding
Francisco Alberto García‐Vázquez
Animal Reproduction Science (2024) Vol. 269, pp. 107538-107538
Open Access | Times Cited: 2
Predicting sow postures from video images: Comparison of convolutional neural networks and segmentation combined with support vector machines under various training and testing setups
Mathieu Bonneau, B. Benet, Yann Labrune, et al.
Biosystems Engineering (2021) Vol. 212, pp. 19-29
Open Access | Times Cited: 14
Classifying active and inactive states of growing rabbits from accelerometer data using machine learning algorithms
Mónica Mora, Lucile Riaboff, Ingrid David, et al.
Smart Agricultural Technology (2024), pp. 100675-100675
Open Access | Times Cited: 1
A Review of Sensors and Machine Learning in Animal Farming
Ahmed Yaseer, Heping Chen
(2021), pp. 747-752
Closed Access | Times Cited: 8
Posture identification for stall-housed sows around estrus using a robotic imaging system
Ziteng Xu, Fengkai Tian, Jing Zhou, et al.
Computers and Electronics in Agriculture (2023) Vol. 211, pp. 107971-107971
Closed Access | Times Cited: 3
The Use of Animal’s Body, Scrotal Temperature and Motion Monitoring in Evaluating Boar Semen Production Capacity
Vasiliki Stravogianni, Theodoros Samaras, C. Boscos, et al.
Animals (2022) Vol. 12, Iss. 7, pp. 829-829
Open Access | Times Cited: 4
Assessment of lying down behaviour in temporarily crated lactating sows
Gudrun Illmann, Sébastien Goumon, Helena Chaloupková
animal (2020) Vol. 15, Iss. 2, pp. 100130-100130
Open Access | Times Cited: 3
Modelling of Animal Activity, Illuminance, and Noise on a Weaned Piglet Farm
María Dolores Garrido Fernández, Roberto Besteiro, Tamara Arango, et al.
Animals (2023) Vol. 13, Iss. 20, pp. 3257-3257
Open Access | Times Cited: 1
Wireless Sensor Node System to Monitor Pig Activities for Behavior Classification
Brandon Cheung, Yuezhong Xu, Dong Sam Ha
2022 IEEE 65th International Midwest Symposium on Circuits and Systems (MWSCAS) (2023), pp. 571-575
Closed Access
Pigs behind the technology : individual activity monitoring to assess resilience in pigs
Lisette Elise van der Zande
(2022)
Open Access
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