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Anomaly Detection
Anomaly Detection is a binary classification identifying unusual or unexpected patterns in a dataset, which deviate significantly from the majority of the data. The goal of anomaly detection is to identify such anomalies, which could represent errors, fraud, or other types of unusual events, and flag them for further investigation.
[Image source]: GAN-based Anomaly Detection in Imbalance Problems
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172개MVTec ADVisAMVTec LOCO ADOne-class CIFAR-10CUHK AvenueShanghaiTechUCR Anomaly ArchiveUCF-CrimeReal 3D-ADFishyscapes L&FXD-ViolenceMPDDShanghaiTech Weakly SupervisedAnoShiftBTADOne-class CIFAR-100HR-ShanghaiTechUBnormalUCSD Ped2MVTEC 3D-ADMVTec ADUnlabeled CIFAR-10 vs CIFAR-100Fashion-MNISTShanghaiTech Weakly SupervisedGoodsADHR-AvenueMVTEC 3D-ADOne-class ImageNet-30UBnormalNumenta Anomaly Benchmark