Search alternatives:
significant point » significant amount (Expand Search), significant part (Expand Search), significant event (Expand Search)
point decrease » point increase (Expand Search)
shape decrease » shape increases (Expand Search), small decrease (Expand Search), showed decreased (Expand Search)
step decrease » sizes decrease (Expand Search), teer decrease (Expand Search), we decrease (Expand Search)
significant point » significant amount (Expand Search), significant part (Expand Search), significant event (Expand Search)
point decrease » point increase (Expand Search)
shape decrease » shape increases (Expand Search), small decrease (Expand Search), showed decreased (Expand Search)
step decrease » sizes decrease (Expand Search), teer decrease (Expand Search), we decrease (Expand Search)
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281
Form for machine recognition.
Published 2025“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”
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282
RMSE versus architectural parameters.
Published 2025“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”
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283
Kalman process.
Published 2025“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”
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284
Attention mechanism.
Published 2025“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”
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Participant’s data including characteristics and primary outcome measurement.
Published 2024Subjects: -
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