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1 maj 2024 · The research results indicate that the best performance in classifying the six behaviors of sheep was achieved using the CNN-LSTM model with the fusion of jaw and leg data at 20 Hz. Therefore, we selected nine sheep and used this model to classify their behaviors throughout the entire experimental period in the plot.
The model was successful at categorising grazing, standing, walking and lying behaviour classes with varying sensitivity, and no significant difference in model accuracy was observed between the three moving window lengths.
7 lip 2022 · We selected the combination (trained stacking model, 3 s time window, T-acc and T-gyr data) with the best classification performance on the CTB test dataset to classify the behavior of three grazing sheep for 7.5 h (from 9:00 a.m. to 4:30 p.m.) each on pasture with three different SSH.
22 lip 2021 · Survey data for the 17 populations were compiled based on agency records that contained information obtained using multiple methods, including fixed-wing and helicopter- and ground-based survey efforts to count animals and classify animals into age and sex classes.
In order to reduce the memory requirement, the lamb data (growth rate, carcass weight, carcass grade, fat% and lamb fleece iveight) were analysed by a reduced multiple-trait animal model including genetic maternal effect.
2 wrz 2021 · This study aimed (i) to classify and characterize farms in representative typologies and (ii) to point out the main factors responsible for the differences between the sheep farm typologies in Brazilian semiarid region.
12 lis 2022 · Smart Sheep Breeder—an artificial intelligence-driven fully functional, multi-use DSS for performance recording, farm data management, breeding, ranking of animals on genetic merit, and...
