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Found 3 papers, 2 papers with code
Understanding patient complaint characteristics using contextual clinical BERT embeddings
In clinical conversational applications, extracted entities tend to capture the main subject of a patient's complaint, namely symptoms or diseases.
Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection
At the test stage, the learned memory will be fixed, and the reconstruction is obtained from a few selected memory records of the normal data.
Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videos
Appearance features have been widely used in video anomaly detection even though they contain complex entangled factors.
Ranked #6 on
Video Anomaly Detection
on HR-UBnormal
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