MeiBRD meta-learns a graph-neural residual deformation function to correct linear biomechanical predictions for intraoperative liver registration from sparse context samples.
IEEE Transactions on Medical Imaging39(6), 2223– 2234 (Jun 2020)
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Hybrid ANN-CANN network for visual object tracking that operationalizes bias-variance complementarity to outperform baselines on nine benchmarks.
citing papers explorer
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MeiBRD: Meta-Learning Intraoperative Biomechanical Residual Deformation
MeiBRD meta-learns a graph-neural residual deformation function to correct linear biomechanical predictions for intraoperative liver registration from sparse context samples.
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A Theory-grounded Hybrid Neural Network Integrating Complementary Estimation Mechanisms for Stable Visual Object TrackingA
Hybrid ANN-CANN network for visual object tracking that operationalizes bias-variance complementarity to outperform baselines on nine benchmarks.