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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:

Behavior classification of goats using 9-axis multi sensors: The effect of imbalanced datasets on classification performance
Koki Sakai, Kazato Oishi, Masafumi MIWA, et al.
Computers and Electronics in Agriculture (2019) Vol. 166, pp. 105027-105027
Closed Access | Times Cited: 51

Showing 1-25 of 51 citing articles:

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
Animal behavior classification via deep learning on embedded systems
Reza Arablouei, Liang Wang, Lachlan Currie, et al.
Computers and Electronics in Agriculture (2023) Vol. 207, pp. 107707-107707
Open Access | Times Cited: 57
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
Classification of broiler behaviours using triaxial accelerometer and machine learning
Xiao Yang, Yang Zhao, Garrett M. Street, et al.
animal (2021) Vol. 15, Iss. 7, pp. 100269-100269
Open Access | Times Cited: 57
Advancements in Bio-inspired Self-Powered Wireless Sensors: Materials, Mechanisms, and Biomedical Applications
Mohammad Ali Farzin, Seyed Morteza Naghib, Navid Rabiee
ACS Biomaterials Science & Engineering (2024) Vol. 10, Iss. 3, pp. 1262-1301
Closed Access | Times Cited: 16
Identifying Sheep Activity from Tri-Axial Acceleration Signals Using a Moving Window Classification Model
Jamie Barwick, David Lamb, Robin Dobos, et al.
Remote Sensing (2020) Vol. 12, Iss. 4, pp. 646-646
Open Access | Times Cited: 47
Hidden Markov models identify major movement modes in accelerometer and magnetometer data from four albatross species
Melinda G. Conners, Théo Michelot, Eleanor I. Heywood, et al.
Movement Ecology (2021) Vol. 9, Iss. 1
Open Access | Times Cited: 34
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
Beyond observation: Deep learning for animal behavior and ecological conservation
Lyes Saad Saoud, Atif Sultan, Mahmoud Elmezain, et al.
Ecological Informatics (2024), pp. 102893-102893
Open Access | Times Cited: 6
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
Using segment-based features of jaw movements to recognise foraging activities in grazing cattle
José O. Chelotti, Sebastián R. Vanrell, Luciano S. Martinez-Rau, et al.
Biosystems Engineering (2023) Vol. 229, pp. 69-84
Open Access | Times Cited: 10
A pipeline with pre-processing options to detect behaviour from accelerometer data using Machine Learning tested on dairy goats.
Sarah Mauny, Joon Kwon, N.C. Friggens, et al.
Peer Community Journal (2025) Vol. 5
Open Access
Behavior Classification and Analysis of Grazing Sheep on Pasture with Different Sward Surface Heights Using Machine Learning
Zhongming Jin, Leifeng Guo, Hang Shu, et al.
Animals (2022) Vol. 12, Iss. 14, pp. 1744-1744
Open Access | Times Cited: 16
Exploring the Potential of Machine Learning Algorithms Associated with the Use of Inertial Sensors for Goat Kidding Detection
Pedro Gonçalves, M.R. Marques, A.T. Belo, et al.
Animals (2024) Vol. 14, Iss. 6, pp. 938-938
Open Access | Times Cited: 3
Ephedra sinica Influences the Grazing Activities of Mixed Grazing Cattle and Sheep in Desert Steppe
Z Zhang, Xiaowei Gou, Yuping Rong, et al.
Land Degradation and Development (2025)
Closed Access
An intelligent method for dairy goat tracking based on Siamese network
Qingguo Su, Jinglei Tang, Mingxin Zhai, et al.
Computers and Electronics in Agriculture (2021) Vol. 193, pp. 106636-106636
Closed Access | Times Cited: 20
Evaluating Behavior Recognition Pipeline of Laying Hens Using Wearable Inertial Sensors
Kaori Fujinami, Ryo Takuno, Itsufumi Sato, et al.
Sensors (2023) Vol. 23, Iss. 11, pp. 5077-5077
Open Access | Times Cited: 8
Behaviour‐specific spatiotemporal patterns of habitat use by sea turtles revealed using biologging and supervised machine learning
Jenna L. Hounslow, Sabrina Fossette, Wei Chong, et al.
Journal of Applied Ecology (2023) Vol. 60, Iss. 9, pp. 1828-1840
Open Access | Times Cited: 8
A Recognition Method for Aggressive Chicken Behavior Based on Machine Learning
Lihua Li, Ziqi Wang, Hou Wang, et al.
IEEE Access (2024) Vol. 12, pp. 24762-24775
Open Access | Times Cited: 2
Classification of Behaviour in Conventional and Slow-Growing Strains of Broiler Chickens Using Tri-Axial Accelerometers
Justine Pearce, Yu‐Mei Chang, Dong Xia, et al.
Animals (2024) Vol. 14, Iss. 13, pp. 1957-1957
Open Access | Times Cited: 2
Applications of Artificial Intelligence for Heat Stress Management in Ruminant Livestock
Ebenezer Binuni Rebez, Veerasamy Sejian, M. V. Silpa, et al.
Sensors (2024) Vol. 24, Iss. 18, pp. 5890-5890
Open Access | Times Cited: 2
Disentangling data dependency using cross-validation strategies to evaluate prediction quality of cattle grazing activities using machine learning algorithms and wearable sensor data
Leonardo Augusto Coelho Ribeiro, Tiago Bresolin, Guilherme J. M. Rosa, et al.
Journal of Animal Science (2021) Vol. 99, Iss. 9
Open Access | Times Cited: 11
Farm Animals’ Behaviors and Welfare Analysis with IA Algorithms: A Review
Olivier Debauche, Meryem Elmoulat, Saïd Mahmoudi, et al.
Revue d intelligence artificielle (2021) Vol. 35, Iss. 3, pp. 243-253
Open Access | Times Cited: 11
Estimation of beef cow body condition score: a machine learning approach using three-dimensional image data and a simple approach with heart girth measurements
Tomoki Kojima, Kazato Oishi, Naoto Aoki, et al.
Livestock Science (2021) Vol. 256, pp. 104816-104816
Closed Access | Times Cited: 10
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