Proceedings
Authors
| Filter results2 paper(s) found. |
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1. Wheat Biomass Estimation Using Visible Aerial Images and Artificial Neural NetworkIn this study, visible RGB-based vegetation indices (VIs) from UAV high spatial resolution (1.9 cm) remote sensing images were used for modeling shoot biomass of two Brazilian wheat varieties (TBIO Toruk and BRS Parrudo). The approach consists of a combination of Artificial Neural Network (ANN) with several Vegetation Indices to model the measured crop biomass at different growth stages. Several vegetation indices were implemented: NGRDI (Normalized Green-Red Difference Index), CIVE (Color Index... M.R. De souza, T.D. Bertani, A. Parraga, C. Bredemeier, C. Trentin, D. Doering, A. Susin, M. Negreiros |
2. Lameness Detection in Dairy Cattle Using GPS and Accelerometers Wearable SensorsLameness significantly impacts cow health and welfare on dairy farms, yet identifying lamecows remains challenging. Wearable sensors like GPS and accelerometers show promise for automated lameness detection, but their effectiveness outdoors is still unclear. Therefore, there are gaps in understanding their applicability and the necessary features for outdoor settings. Additionally, it is uncertain whether environmental factors, such as temperature and time of day, influence their the model performance,... N. Mhlongo, H. De knegt, W.F. De boer, F. Van langevelde |