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A review on computer vision systems in monitoring of poultry: A welfare perspective

Artificial Intelligence in Agriculture 2020年第1期4卷 184-208页

作者： Cedric Okinda Innocent Nyalala Tchalla Korohou Celestine Okinda Jintao Wang tracy achieng Patrick Wamalwa Tai Mang Mingxia Shen College of Artificial Intelligence Laboratory ofModern Facility Agriculture Technology and Equipment Engineering of Jiangsu ProvinceNanjing Agricultural UniversityJiangsu 210031PR China College of Veterinary Science and Agriculture University of NairobiLower KabeteNairobiKenya Faculty of Bioscience and Engineering Ghent UniversityGhentBelgium Faculty of Engineering Department of Agricultural EngineeringEgerton UniversityNjoroKenya

Monitoring of poultry welfare-related bio-processes and bio-responses is vital in welfare assessment and management of welfare-related *** the current development in information technologies,computer vision has become a promising tool in the real-time automation of poultry monitoring systems due to its non-intrusive and non-invasive properties,and its ability to present a wide range of ***,it can be applied to monitor several bio-processes and *** review summarizes the current advances in poultrymonitoring techniques based on computer vision systems,i.e.,conventional machine learning-based and deep learning-based systems.A detailed presentation on the machine learning-based system was presented,i.e.,pre-processing,segmentation,feature extraction,feature selection,and dimension reduction,and ***,deep learning approaches in poultry monitoring were also ***,the challenges and possible solutions presented by researches in poultry monitoring,such as variable illumination conditions,occlusion problems,and lack of augmented and labeled poultry datasets,were discussed.

关键词： Computer vision Deep learning Machine learning Monitoring Poultry Welfare

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