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Abstract
Abstract The behaviours of the pig are often closely related to their health. Pig recognition is very important for pig behaviour analysis and digital breeding. Currently, the early signs and abnormal behaviours of sick pigs in breeding farms are mainly completed by human observation. However, visual inspection is labour intensive and time-consuming, and it suffers from the problems of individual experiences and varying environments. An improved ResNet model was proposed and applied to detect individual pigs in this study based on deep learning knowledge. The developed model captured the features of pigs applying across layer connections, and the ability of feature expression was improved by adding a new residual module. The number of layers was reduced to minimise the net complexity. Generally, the ResNet frame was developed by reducing the number of convolution layers, constructing different types of the residual module and adding the number of convolution kernels. The training accuracy and testing accuracy reached 98.2% and 96.4%, respectively, when using the improved model. The experiment results showed that the method proposed in this paper for checking living situations and disease prevention of commercial pigs in pig farms is potential.
Highlights
Individual pig recognition is very important for pig behaviour analysis and digital breeding
This paper presents an improved RESNET model based on deep learning for individual pig detection
The improved RESNET model in this paper is compact with 32 convolution layers, and 3*3 convolution kernels are used in all convolution layers [17]
Summary
Individual pig recognition is very important for pig behaviour analysis and digital breeding. It has been demonstrated that if a pig keeps constant postures such as standing with a raising head or laying for a longer time, it is likely tired or ill [1]. A further health check up and proper treatment are necessary in this case. If the pig keeps standing with its head raising, the pig could be stimulated and disturbed leading to panic or fear by the external environment. It is necessary to examine the environment of the pig farm. To study the behaviour of pigs, the first step is to detect the pig target. The living situation and disease prevention of ISSN 2444-8656 doi:10.2478/amns.2021.2.00040
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