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Found 5 papers, 4 papers with code
When eBPF Meets Machine Learning: On-the-fly OS Kernel Compartmentalization
Compartmentalization effectively prevents initial corruption from turning into a successful attack.
Alternate Diverse Teaching for Semi-supervised Medical Image Segmentation
To mitigate the confirmation bias from the diverse supervision, the core of AD-MT lies in two proposed modules: the Random Periodic Alternate (RPA) Updating Module and the Conflict-Combating Module (CCM).
Clean Label Disentangling for Medical Image Segmentation with Noisy Labels
Current methods focusing on medical image segmentation suffer from incorrect annotations, which is known as the noisy label issue.
Progressive Target-Styled Feature Augmentation for Unsupervised Domain Adaptation on Point Clouds
Unlike previous works that focus on feature extractor adaptation, our PTSFA approach focuses on classifier adaptation.
Conflict-Based Cross-View Consistency for Semi-Supervised Semantic Segmentation
In this work, we propose a new conflict-based cross-view consistency (CCVC) method based on a two-branch co-training framework which aims at enforcing the two sub-nets to learn informative features from irrelevant views.
