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Found 5 papers, 2 papers with code
Composite Layers for Deep Anomaly Detection on 3D Point Clouds
Moreover, our CompositeNets substantially outperform existing solutions for anomaly detection on point clouds.
Deep Open-Set Recognition for Silicon Wafer Production Monitoring
Here we address WDM monitoring as an open-set recognition problem to accurately classify WDM in known categories and promptly detect novel patterns.
Nonparametric and Online Change Detection in Multivariate Datastreams using QuantTree
Like many change-detection algorithms, QT-EWMA builds a model of the data distribution, in our case a QuantTree histogram, from a stationary training set.
QuantTree: Histograms for Change Detection in Multivariate Data Streams
Our experiments show that the proposed histograms are very effective in detecting changes in high dimensional data streams, and that the resulting thresholds can effectively control the false positive rate, even when the number of training samples is relatively small.
Change Detection in Multivariate Datastreams: Likelihood and Detectability Loss
We address the problem of detecting changes in multivariate datastreams, and we investigate the intrinsic difficulty that change-detection methods have to face when the data dimension scales.
