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Ulm University of Applied Sciences
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Classifying exercise repetitions with label distributions reveals ambiguity that traditional one-hot methods overlook, leading to more accurate assessments in home-based physiotherapy.
A lightweight U-Net achieves superior performance to diffusion models in estimating MRI-SFF while slashing inference time by over 200 times.
