GMENet synthesizes missing MRI sequences with gated cross-attention and fuses dual-sequence features via confidence-aware mixture-of-experts for improved glioma diagnosis on incomplete multi-center data.
Deep long-tailed learn- ing: A survey.IEEE transactions on pattern analysis and machine intelligence, 45(9):10795–10816,
2 Pith papers cite this work. Polarity classification is still indexing.
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MCAT improves adversarial robustness on long-tailed datasets by constraining examples to class manifolds and enforcing balanced geometric separation.
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GMENet: Generative Mixture of Experts Network for Multi-Center Glioma Diagnosis with Incomplete Imaging Sequences
GMENet synthesizes missing MRI sequences with gated cross-attention and fuses dual-sequence features via confidence-aware mixture-of-experts for improved glioma diagnosis on incomplete multi-center data.
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Manifold-Constrained Adversarial Training for Long-Tailed Robustness via Geometric Alignment
MCAT improves adversarial robustness on long-tailed datasets by constraining examples to class manifolds and enforcing balanced geometric separation.