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Found 4 papers, 2 papers with code
MuSc: Zero-Shot Industrial Anomaly Classification and Segmentation with Mutual Scoring of the Unlabeled Images
We reveal that the abundant normal and abnormal cues implicit in unlabeled test images can be exploited for anomaly determination, which is ignored by prior methods.
Towards Human-like Perception: Learning Structural Causal Model in Heterogeneous Graph
Heterogeneous graph neural networks have become popular in various domains.
Community-Based Hierarchical Positive-Unlabeled (PU) Model Fusion for Chronic Disease Prediction
Positive-Unlabeled (PU) Learning is a challenge presented by binary classification problems where there is an abundance of unlabeled data along with a small number of positive data instances, which can be used to address chronic disease screening problem.
Transaction Fraud Detection Using GRU-centered Sandwich-structured Model
Rapid growth of modern technologies such as internet and mobile computing are bringing dramatically increased e-commerce payments, as well as the explosion in transaction fraud.
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