Methods and challenges in computer vision-based livestock anomaly detection, a systematic review
Authors:
- Yutong DengYDYutong Deng
- Hongchun QuHongchun Qu
- Ansong LengALAnsong Leng
- Xiaoming TangXTXiaoming Tang
- Shidong ZhaiShidong Zhai
- 3 April 2025
- journal article
- review article
- Published by Elsevier in Biosystems Engineering
- Vol. 253
Abstract
No abstract availableFunding Information
- Chongqing Municipal Science and Technology Bureau
- Chongqing University of Posts and Telecommunications
This publication has 130 references indexed in Scilit:
- Going Deeper than Tracking: A Survey of Computer-Vision Based Recognition of Animal Pain and EmotionsInternational Journal of Computer Vision, 2022
- Individual identification of cashmere goats via method of fusion of multiple optimizationComputer Animation and Virtual Worlds, 2022
- Recognition of imbalanced underwater acoustic datasets with exponentially weighted cross-entropy lossApplied Acoustics, 2021
- RETRACTED ARTICLE: Improving the prediction rate of unusual behaviors of animal in a poultry using deep learning techniqueSoft Computing, 2020
- Prospects for sustainability of pig production in relation to climate change and novel feed resourcesJournal of the Science of Food and Agriculture, 2020
- Real-time recognition of cattle using animal biometricsJournal of Real-Time Image Processing, 2016
- The long and short of it: A review of tail docking in farm animalsApplied Animal Behaviour Science, 2011
- Behavioural predictors of the start of normal and dystocic calving in dairy cows and heifersApplied Animal Behaviour Science, 2011
- Expressing pain: The communication and interpretation of facial pain signalsJournal of Nonverbal Behavior, 1995
- Support-vector networksMachine Learning, 1995