Deep transfer learning in sheep activity recognition using accelerometer data

Natasa Kleanthous, Abir Hussain, Wasiq Khan, Jennifer Sneddon, Panos Liatsis

Abstract: Highlights•Monitoring animals through human observation is time consuming and labour intensive.•Smart devices mounted on the animals, embedded with predictive models are needed.•Dataset diversity using two types of accelerometers attached to animals’ collars.•Convolutional Neural Networks to predict active, grazing, and inactive behaviours.•Use of Transfer learning to evaluate the generalization of the pre-trained model.