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SLADE: Detecting Dynamic Anomalies in Edge Streams without Labels via Self-Supervised Learning
In this paper, we propose SLADE (Self-supervised Learning for Anomaly Detection in Edge Streams) for rapid detection of dynamic anomalies in edge streams, without relying on labels.
Deep-neural-network based sinogram synthesis for sparse-view CT image reconstruction
Recently, a number of approaches to low-dose computed tomography (CT) have been developed and deployed in commercialized CT scanners.
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