Liang Guo
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PaCo-VLA introduces a passivity-shielded compliance prior to safely bridge the gap between high-level Vision-Language-Action (VLA) semantic outputs and low-level, force-sensitive robotic control.
The paper proposes GloResNet, a lightweight 3D CNN that effectively predicts brain injury in preterm infants using T2-weighted MRI, achieving an average accuracy of 75.18%.
Papers
GloResNet: A lightweight 3D CNN with global topological features for preterm brain injury prediction
Boyu Yuan, Jiamiao Lu, Weichuan Zhang, Benqing Wu +4 more
The paper proposes GloResNet, a lightweight 3D CNN that effectively predicts brain injury in preterm infants using T2-weighted MRI, achieving an average accuracy of 75.18%.