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Found 3 papers, 1 papers with code
Multimodal sensor data fusion for in-situ classification of animal behavior using accelerometry and GNSS data
However, the multimodal animal behavior classification algorithm based on posterior probability fusion is preferable to the one based on feature concatenation as it delivers better classification accuracy, has less computational and memory complexity, is more robust to sensor data failure, and enjoys better modularity.
Animal Behavior Classification via Accelerometry Data and Recurrent Neural Networks
We study the classification of animal behavior using accelerometry data through various recurrent neural network (RNN) models.
Animal behavior classification via deep learning on embedded systems
We develop an end-to-end deep-neural-network-based algorithm for classifying animal behavior using accelerometry data on the embedded system of an artificial intelligence of things (AIoT) device installed in a wearable collar tag.
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