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for Pollinator Monitoring: Train and optimise deep learning models for pollinator detection and classification using annotated image datasets. Post-processing object tracking algorithms will be incorporated
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very well the behaviour of these cryogenic hydrogen pumps, in order to master their integration into the hydrogen system. The primary objective of this research in collaboration with Airbus is to develop
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substrate, enabling the layer-by-layer construction of complex 3D objects. The temperature field created by the interaction between the electric arc and the material is a critical factor influencing the
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involves feeding a metal filler wire, either coaxially or off-axis, into an electric arc to create a molten pool that solidifies on a substrate, enabling the layer-by-layer construction of 3D objects
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of their machines is maximised, or machine downtime is minimised. The aim is to develop a smart sensor prototype and demonstrator for condition monitoring of low-speed bearings. The following objectives are defined