Why do Angular Margin Losses work well for Semi-Supervised Anomalous Sound Detection?
Kevin WilkinghoffFrank KurthPublished in: CoRR (2023)
Keyphrases
- semi supervised
- anomaly detection
- detecting anomalous
- detection method
- detection algorithm
- maximum margin
- detection accuracy
- false alarms
- unlabeled data
- multi view
- semi supervised learning
- automatic detection
- neural network
- false positives
- event detection
- detection rate
- support vector
- machine learning
- supervised learning
- objective function
- training data
- semi supervised classification
- detect anomalies