Auto-generated label distributions let IMU exercise networks match one-hot classification while more reliably detecting ambiguous borderline repetitions and their competing classes.
Do digital interventions increase adherence to home exercise rehabilitation? A systematic review of randomised controlled trials
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Representing and Detecting Label Ambiguity in IMU-Based Exercise Evaluation
Auto-generated label distributions let IMU exercise networks match one-hot classification while more reliably detecting ambiguous borderline repetitions and their competing classes.