2015 Ieee Sensors 2015
DOI: 10.1109/icsens.2015.7370529
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A study of sensor derived features in cattle behaviour classification models

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Cited by 16 publications
(19 citation statements)
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“…Recent studies acknowledge the potential of collaring applications and have evaluated offline activity recognition of cows [7,9,14,25,48], sheep [24,46], and vultures [31]. Smith et al [44] studied features in cattle behavior models, using a greedy search to identify feature subsets that were most effective in classifying activities of steers. The authors elaborated on this work [45] and classified five general activities of dairy cows.…”
Section: Related Workmentioning
confidence: 99%
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“…Recent studies acknowledge the potential of collaring applications and have evaluated offline activity recognition of cows [7,9,14,25,48], sheep [24,46], and vultures [31]. Smith et al [44] studied features in cattle behavior models, using a greedy search to identify feature subsets that were most effective in classifying activities of steers. The authors elaborated on this work [45] and classified five general activities of dairy cows.…”
Section: Related Workmentioning
confidence: 99%
“…Embedded feature selection was used to select a subset of features that produced the best performance for each activity. The orientation of the sensor attached to the cows was fixed in both studies [44,45] and the authors did not consider orientation-dependency. The goal of the work presented here is to find features that are orientation-independent, to evaluate these features on various classifiers, and to investigate the impact of the feature-subset size.…”
Section: Related Workmentioning
confidence: 99%
“…In the state of the art, most AAR approaches attempt to infer activity from bodymotion using inertial measurement units (IMUs). Researchers have used IMUs for AAR of various types of animals including wildlife [121,152,168,187], livestock [21,38,156], and pets [53,87,181]. An IMU generally consists of an accelerometer, gyroscope, and magnetometer which measure acceleration, angular velocity, and magnetism.…”
Section: Introductionmentioning
confidence: 99%
“…Table 2.2 shows that different studies interpret behaviors differently or make different choices in terms of granularity. For example, one study only defined grooming [156], while another subdivided grooming into actor and receiving [42]. The mean number of activities that is separated is 5.…”
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confidence: 99%
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