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MAMA Net: Multi-scale Attention Memory Autoencoder Network for Anomaly Detection
2020
IEEE Transactions on Medical Imaging
Anomaly detection refers to the identification of cases that do not conform to the expected pattern, which takes a key role in diverse research areas and application domains. Most of existing methods can be summarized as anomaly object detection-based and reconstruction error-based techniques. However, due to the bottleneck of defining encompasses of real-world high-diversity outliers and inaccessible inference process, individually, most of them have not derived groundbreaking progress. To
doi:10.1109/tmi.2020.3045295
fatcat:elicefjf45hunafl7oamhvx2na