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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:

Mounting Behaviour Recognition for Pigs Based on Deep Learning
Dan Li, Yifei Chen, Kaifeng Zhang, et al.
Sensors (2019) Vol. 19, Iss. 22, pp. 4924-4924
Open Access | Times Cited: 62

Showing 1-25 of 62 citing articles:

Behaviour recognition of pigs and cattle: Journey from computer vision to deep learning
Chen Chen, Weixing Zhu, Tomás Norton
Computers and Electronics in Agriculture (2021) Vol. 187, pp. 106255-106255
Open Access | Times Cited: 132
Artificial intelligence in animal farming: A systematic literature review
Jun Bao, Qiuju Xie
Journal of Cleaner Production (2021) Vol. 331, pp. 129956-129956
Closed Access | Times Cited: 132
Practices and Applications of Convolutional Neural Network-Based Computer Vision Systems in Animal Farming: A Review
Guoming Li, Yanbo Huang, Zhiqian Chen, et al.
Sensors (2021) Vol. 21, Iss. 4, pp. 1492-1492
Open Access | Times Cited: 127
Non-contact sensing technology enables precision livestock farming in smart farms
Maosong Yin, Ruiqin Ma, Hailing Luo, et al.
Computers and Electronics in Agriculture (2023) Vol. 212, pp. 108171-108171
Closed Access | Times Cited: 45
Application of deep learning for livestock behaviour recognition: A systematic literature review
Ali Rohan, Muhammad Saad Rafaq, Md Junayed Hasan, et al.
Computers and Electronics in Agriculture (2024) Vol. 224, pp. 109115-109115
Open Access | Times Cited: 18
PBR-YOLO: A lightweight piglet multi-behavior recognition algorithm based on improved yolov8
Yizhi Luo, Kai Lin, Zixuan Xiao, et al.
Smart Agricultural Technology (2025), pp. 100785-100785
Open Access | Times Cited: 2
The livestock farming digital transformation: implementation of new and emerging technologies using artificial intelligence
Sigfredo Fuentes, Claudia Gonzalez Viejo, Eden Tongson, et al.
Animal Health Research Reviews (2022) Vol. 23, Iss. 1, pp. 59-71
Open Access | Times Cited: 62
ASAS-NANP SYMPOSIUM: Applications of machine learning for livestock body weight prediction from digital images
Zhuoyi Wang, Saeed Shadpour, Esther T. Chan, et al.
Journal of Animal Science (2021) Vol. 99, Iss. 2
Open Access | Times Cited: 59
The Research Progress of Vision-Based Artificial Intelligence in Smart Pig Farming
Shunli Wang, Honghua Jiang, Yongliang Qiao, et al.
Sensors (2022) Vol. 22, Iss. 17, pp. 6541-6541
Open Access | Times Cited: 45
The quest to develop automated systems for monitoring animal behavior
Janice M. Siegford, Juan P. Steibel, Junjie Han, et al.
Applied Animal Behaviour Science (2023) Vol. 265, pp. 106000-106000
Open Access | Times Cited: 25
KABR: In-Situ Dataset for Kenyan Animal Behavior Recognition from Drone Videos
Maksim Kholiavchenko, Jenna Kline, Michelle Ramírez, et al.
(2024), pp. 31-40
Closed Access | Times Cited: 13
Technological Tools and Artificial Intelligence in Estrus Detection of Sows—A Comprehensive Review
Md Sharifuzzaman, Hong‐Seok Mun, Keiven Mark B. Ampode, et al.
Animals (2024) Vol. 14, Iss. 3, pp. 471-471
Open Access | Times Cited: 9
Automatic behavior recognition of group-housed goats using deep learning
Min Jiang, Yuan Rao, Jingyao Zhang, et al.
Computers and Electronics in Agriculture (2020) Vol. 177, pp. 105706-105706
Closed Access | Times Cited: 67
A review of video-based pig behavior recognition
Qiumei Yang, Deqin Xiao
Applied Animal Behaviour Science (2020) Vol. 233, pp. 105146-105146
Closed Access | Times Cited: 67
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
The Application of Cameras in Precision Pig Farming: An Overview for Swine-Keeping Professionals
Elanchezhian Arulmozhi, Anil Bhujel, Byeong-Eun Moon, et al.
Animals (2021) Vol. 11, Iss. 8, pp. 2343-2343
Open Access | Times Cited: 45
Basic motion behavior recognition of single dairy cow based on improved Rexnet 3D network
Shuaifei Ma, Qianru Zhang, Tengfei Li, et al.
Computers and Electronics in Agriculture (2022) Vol. 194, pp. 106772-106772
Closed Access | Times Cited: 33
Automated Video Behavior Recognition of Pigs Using Two-Stream Convolutional Networks
Kaifeng Zhang, Dan Li, Jiayun Huang, et al.
Sensors (2020) Vol. 20, Iss. 4, pp. 1085-1085
Open Access | Times Cited: 45
A Machine Vision-Based Method for Monitoring Scene-Interactive Behaviors of Dairy Calf
Yangyang Guo, Dongjian He, Lilong Chai
Animals (2020) Vol. 10, Iss. 2, pp. 190-190
Open Access | Times Cited: 40
Pig mounting behaviour recognition based on video spatial–temporal features
Qiumei Yang, Deqin Xiao, Jiahao Cai
Biosystems Engineering (2021) Vol. 206, pp. 55-66
Closed Access | Times Cited: 37
Detection Method of Cow Estrus Behavior in Natural Scenes Based on Improved YOLOv5
Rong Wang, Zongzhi Gao, Qifeng Li, et al.
Agriculture (2022) Vol. 12, Iss. 9, pp. 1339-1339
Open Access | Times Cited: 27
An Improved Pig Counting Algorithm Based on YOLOv5 and DeepSORT Model
Yigui Huang, Deqin Xiao, Junbin Liu, et al.
Sensors (2023) Vol. 23, Iss. 14, pp. 6309-6309
Open Access | Times Cited: 14
A Monitoring System for Cattle Behavior Detection using YOLO-v8 in IoT Environments
Kyungchang Jeong, D.G. Kim, Jae-Hyen Ryu, et al.
2023 IEEE International Conference on Consumer Electronics (ICCE) (2024), pp. 1-4
Closed Access | Times Cited: 5
A Spatiotemporal Convolutional Network for Multi-Behavior Recognition of Pigs
Dan Li, Kaifeng Zhang, Zhenbo Li, et al.
Sensors (2020) Vol. 20, Iss. 8, pp. 2381-2381
Open Access | Times Cited: 36
Automated detection and analysis of piglet suckling behaviour using high-accuracy amodal instance segmentation
Haiming Gan, Mingqiang Ou, Chengpeng Li, et al.
Computers and Electronics in Agriculture (2022) Vol. 199, pp. 107162-107162
Closed Access | Times Cited: 22
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