Evaluation of sampling frequency, window size and sensor position for classification of sheep behaviour

Abstract

Automated behavioural classification and identification through sensors has the potential to improve health and welfare of the animals. Position of a sensor, sampling frequency and window size of segmented signal data has a major impact on classification accuracy in activity recognition and energy needs for the sensor, yet, there are no studies in precision… (More)
DOI: 10.1098/rsos.171442

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