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Recognition of feeding behaviour of pigs and determination of feeding time of each pig by a video-based deep learning method

Chen Chen, Weixing Zhu, Juan Steibel, Janice Siegford, Junjie Han, Tomas Norton
2020 Computers and Electronics in Agriculture  
The aim of this study was to develop a video-based deep learning algorithm to recognise feeding behaviour of nursery pigs and determine the feeding time of pigs on an individual level.  ...  The results indicate that the proposed method can be used to recognise feeding behavior of pigs and determine feeding time of each pig.  ...  Acknowledgements This work was a part of the project funded by the "National Natural Science Foundation of China", China (grant number: 31872399), the "USDA National Institute of Food and Agriculture",  ... 
doi:10.1016/j.compag.2020.105642 fatcat:aqydbfb3nre4zckkin3qoy3vqy

Automatic recognition of feeding and foraging behaviour in pigs using deep learning

Ali Alameer, Ilias Kyriazakis, Hillary A. Dalton, Amy L. Miller, Jaume Bacardit
2020 Biosystems Engineering  
To tackle these problems, we have developed a robust, deep learning-based feeding detection method that (a) does not rely on pig tracking and (b) is capable of distinguishing between feeding and NNV for  ...  Consummatory behaviour Deep learning Pig behaviour Feeding, Foraging Automated, vision-based early warning systems have been developed to detect behavioural changes in groups of pigs to monitor their health  ...  Acknowledgements The animal trial was supported by the Biotechnology  ... 
doi:10.1016/j.biosystemseng.2020.06.013 fatcat:m3nmb5hqdjcz3lpqztl7cklxse

A deep learning-based approach for feeding behavior recognition of weanling pigs

MinJu Kim, YoHan Choi, JeongNam Lee, SooJin Sa, HyunChong Cho
2021 Journal of Animal Science and Technology  
This paper proposes a real-time technique for the detection and recognition of small pigs using a deep-leaning-based method.  ...  The early detection of feed refusal is crucial for the control of disease in the initial stages and the detection of empty feeders for adding feed in a timely manner.  ...  Acknowledgements This study was supported by 2021 the RDA Fellowship Program of National Institute of Animal Science, Rural Development Administration, Korea.  ... 
doi:10.5187/jast.2021.e127 pmid:34957458 pmcid:PMC8672269 fatcat:7crqkp77qvhjbbuxfzbblifc6a

Mounting Behaviour Recognition for Pigs Based on Deep Learning

Dan Li, Yifei Chen, Kaifeng Zhang, Zhenbo Li
2019 Sensors  
in recognition of mounting behaviour.  ...  Subsequently, the eigenvectors were classified with a kernel extreme learning machine (KELM) to determine whether mounting behaviour has occurred.  ...  Considering the information limitations of visual images, the deep image can be an alternative for further research into detecting mounting behaviour. The result should be even more impressive.  ... 
doi:10.3390/s19224924 pmid:31726724 pmcid:PMC6891703 fatcat:a6mqmtdlbneq3mkt2fwm5gfobq

A computer vision approach for recognition of the engagement of pigs with different enrichment objects

Chen Chen, Weixing Zhu, Maciej Oczak, Kristina Maschat, Johannes Baumgartner, Mona Lilian Vestbjerg Larsen, Tomas Norton
2020 Computers and Electronics in Agriculture  
Therefore, aim of this study was to develop a computer vision based approach that utilised a recurrent neural network-based deep learning algorithm to recognise pig enrichment engagement (EE) behaviours  ...  These results indicate that the proposed method can be used to recognise EE behaviours of pigs, and halving the radius of the region of interest can improve the recognition accuracy of EE behaviours.  ...  This work was also a part of the "Auto Play Pig" project funded by the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement (grant number: 842555  ... 
doi:10.1016/j.compag.2020.105580 fatcat:sqb4b7xnjnccbh3fo6xwg6apne

DigiPig: First Developments of an Automated Monitoring System for Body, Head and Tail Detection in Intensive Pig Farming

Marko Ocepek, Anja Žnidar, Miha Lavrič, Dejan Škorjanc, Inger Lise Andersen
2021 Agriculture  
The aim in the first part of the study was to recognize individual pigs (in lying and standing positions) in groups and their body parts (head/ears, and tail) by using machine learning algorithms (feature  ...  Our dataset (n = 583 images, 7579 pig posture) was annotated in Labelbox from 2D video recordings of groups (n = 12–15) of weaned pigs.  ...  We are especially grateful to the DIGI pig group (Ingrid Melkild and Kristine Hov Martinsen) for their support of this work. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/agriculture12010002 fatcat:ijwcak2kknh55b7ulnotrgh7ju

A computer vision-based method for spatial-temporal action recognition of tail-biting behaviour in group-housed pigs

Dong Liu, Maciej Oczak, Kristina Maschat, Johannes Baumgartner, Bernadette Pletzer, Dongjian He, Tomas Norton
2020 Biosystems Engineering  
Taking a computer-vision based approach, in this study, we have developed a novel method to automatically identify and locate tail-biting interactions in group-housed pigs.  ...  In total, our proposed method is capable to identify and locate 89.23% of tail-biting behaviour in group-housed pigs.  ...  As a deep-learning based approach, 247 tail-biting events from 8 h raw video may seem insufficient to train a deep network.  ... 
doi:10.1016/j.biosystemseng.2020.04.007 fatcat:uyeenu6bcngllluex77ysvfkou

Automated recognition of postures and drinking behaviour for the detection of compromised health in pigs

Ali Alameer, Ilias Kyriazakis, Jaume Bacardit
2020 Scientific Reports  
Here, two deep learning-based detector methods were developed to identify pig postures and drinking behaviours of group-housed pigs.  ...  Changes in pig behaviours are a useful aid in detecting early signs of compromised health and welfare.  ...  In addition to detecting individual pig locations and behaviours, the generated profiles comprised of locomotion activities such as relative speed and distance.  ... 
doi:10.1038/s41598-020-70688-6 pmid:32788633 fatcat:rdrof3wkibfrvornyjzmmfng4i

Welfare Health and Productivity in Commercial Pig Herds

Przemysław Racewicz, Agnieszka Ludwiczak, Ewa Skrzypczak, Joanna Składanowska-Baryza, Hanna Biesiada, Tomasz Nowak, Sebastian Nowaczewski, Maciej Zaborowicz, Marek Stanisz, Piotr Ślósarz
2021 Animals  
The need to maintain a high health status of pig herds by eliminating the frequency of different disease units and reducing the need for antimicrobial substances is part of a broadly understood high potential  ...  Automated, innovative early warning systems based on continuous monitoring of specific physiological (e.g., body temperature) and behavioural parameters can provide an alternative to direct diagnosis and  ...  [84] proposed a method to identify sick pigs in real time by analysing the sound of coughing, with a recognition accuracy of 85%.  ... 
doi:10.3390/ani11041176 pmid:33924224 fatcat:zvc473varzckje32ksvfp4d3q4

A spatio-temporal recurrent network for salmon feeding action recognition from underwater videos in aquaculture

Håkon Måløy, Agnar Aamodt, Ekrem Misimi
2019 Computers and Electronics in Agriculture  
Inspired by these application domains and research challenges we introduce a deep video classification network for action recognition of salmon from underwater videos.  ...  On the other hand, the application of deep learning for action or behaviour recognition in other domains such as animal or livestock is comparatively limited.  ...  Acknowledgments This work is supported by the Intelligent Project. The authors gratefully acknowledge the SINTEF Ocean RACE program and its chairman Dr.  ... 
doi:10.1016/j.compag.2019.105087 fatcat:yvjpbboslbeghdtncs7skdilrq

Oestrus Analysis of Sows Based on Bionic Boars and Machine Vision Technology

Kaidong Lei, Chao Zong, Xiaodong Du, Guanghui Teng, Feiqi Feng
2021 Animals  
This study proposes a method and device for the intelligent mobile monitoring of oestrus on a sow farm, applied in the field of sow production.  ...  This approach can more accurately obtain the oestrus duration of a sow and provide a scientific reference for a sow's conception time.  ...  The SAE neural network technology is an efficient and unsupervised feature learning and deep learning classification method.  ... 
doi:10.3390/ani11061485 pmid:34063888 fatcat:6sd2h53xnnglzcx7y2b635udga

Automated Individual Pig Localisation, Tracking And Behaviour Metric Extraction Using Deep Learning

Jake Cowton, Ilias Kyriazakis, Jaume Bacardit
2019 IEEE Access  
We combine a deep CNN object localisation method, Faster Region-based convolutional neural network (R-CNN), with two potential real-time multi-object tracking methods in order to create a complete system  ...  By doing so we can monitor individual pig behaviour changes over time and use these as indicators of health and well-being, which, in turn, will assist in the early detection of disease allowing for earlier  ...  ACKNOWLEDGEMENTS This work was conducted under the Feed-a-Gene project.  ... 
doi:10.1109/access.2019.2933060 fatcat:46bpgr2b7bhjfl7skwbv4qnize

Operant technology applied to solving farm animal problems. An assessment

R. Kilgour, T.M. Foster, W. Temple, L.R. Matthews, K.J. Bremner
1991 Applied Animal Behaviour Science  
The project was supported by funds of the Federal Ministry of Food, Agriculture and Consumer Protection (BMELV) based on a decision of the Parliament of the Federal Republic of Germany via the Federal  ...  The project was supported by funds of the Federal Ministry of Food and Agriculture (BMEL) based on a decision of the Parliament of the Federal Republic of Germany via the Federal Office for Agriculture  ...  This could be achieved by additional light barriers or different contactless sensor technologies such as video based methods.  ... 
doi:10.1016/0168-1591(91)90092-c fatcat:lofxtjyapreotliosuuj7dcip4

A Cost-Effective Pigsty Monitoring System Based on a Video Sensor

2014 KSII Transactions on Internet and Information Systems  
From the experimental results with the video monitoring data obtained from two pig farms, we believe our method based on circadian rhythm can be applied for detecting management problems of group-housed  ...  In this paper, we propose an automated solution for measuring the daily-life activities of pigs by using video data in order to manage the group-housed pigs.  ...  If a farm worker provides food manually, healthy pigs may show some motion at feeding time and it is easy to identify any pigs which are motionless at the feeding time.  ... 
doi:10.3837/tiis.2014.04.018 fatcat:v477fmydi5dsvivniyks76xyry

Automatic individual pig detection and tracking in surveillance videos [article]

Lei Zhang, Helen Gray, Xujiong Ye, Lisa Collins, Nigel Allinson
2018 arXiv   pre-print
Individual pig detection and tracking is an important requirement in many video-based pig monitoring applications.  ...  To tackle these problems, we propose a robust real time multiple pig detection and tracking method which does not require manual marking or physical identification of the pigs, and works under both daylight  ...  , which is supported by BBSRC, NERC, ESRC and the Scottish Government.  ... 
arXiv:1812.04901v1 fatcat:ul64eyyvbbbyvgltag36qb3dgq
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