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Anomalous Sound Detection Using a Binary Classification Model and Class Centroids
Our results showed that multi-task learning using binary classification and metric learning to consider the distance from each class centroid in the feature space is effective, and performance can be significantly improved by using even a small amount of anomalous data during training.
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