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A study is presented comparing the effectiveness of unsupervised feature representations with handcrafted features for cattle behaviour classification. Precision management of cattle requires the interaction of individual animals to be continuously monitored on the farm. Consequently, classifiers are trained to infer the behaviour of the animals using the observations from the sensors that are fitted...
The detection of heat (estrus) events in pasture-based dairy cows fitted with on-animal sensors was investigated using an unsupervised learning. Accelerometer data from the cow collar sensors were used in this approach where the aim was to identify increased activity level (restlessness, increased walking for mating) and to find association with recorded heat events. High dimensional time series data...
Models were developed to classify six different behaviours for a group of seven steers fitted with an accelerometer and pressure sensor. As part of the process, a greedy feature selection method was used to identify the most discriminatory inputs from a diverse set of statistical, spectral and information theory based features. The study showed the second order statistic features (standard deviation...
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