A biomimetic robotic joint shows Type I joint receptors can provide proprioceptive sensing with less than 2 degrees average error in bending and twisting motions.
In Guyon, I.et al.(eds.)Advances in Neural Information Processing Systems, vol
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A 3D self-supervised foundation model trained on over 360k head CT scans improves downstream disease classification on limited-label internal and external datasets versus scratch-trained and prior models.
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Exploring the proprioceptive potential of joint receptors using a biomimetic robotic joint
A biomimetic robotic joint shows Type I joint receptors can provide proprioceptive sensing with less than 2 degrees average error in bending and twisting motions.
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3D Foundation Model for Generalizable Disease Detection in Head Computed Tomography
A 3D self-supervised foundation model trained on over 360k head CT scans improves downstream disease classification on limited-label internal and external datasets versus scratch-trained and prior models.