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GANs for Anomaly Detection
Anomaly detection using GANs is an emerging research field. Anomaly detection using GANs is an emerging research field. Detecting and correctly classifying something unseen as... -
Fashion-MNIST, MNIST, SVHN, dSprites, and CIFAR-10
The dataset used in the paper is Fashion-MNIST, MNIST, SVHN, dSprites, and CIFAR-10. -
NSL-KDD dataset
The NSL-KDD dataset is a comprehensive collection of network traffic data containing both normal and various attack instances. -
Industrial dataset
The industrial dataset is collected from the user log data of one of the most renowned local life information and trading platforms in China. We extract a total of 21 scenarios... -
UCSD Pedestrian dataset
A benchmark dataset for anomaly detection in crowded scenes -
Synthetic dataset for medical image diagnostics
The dataset used in this study is a synthetic dataset for medical image diagnostics. It contains 1000 normal images and 1000 anomaly images. The normal images are generated... -
Synthetic Data Set
The dataset generated by the method of moments (MoM) for training supervised NeuralBIM. -
Graph Fairing Convolutional Networks for Anomaly Detection
Graph Fairing Convolutional Networks for Anomaly Detection -
Water-tank system
The Water-tank system dataset contains observations of two variables: water level and flow rate. -
High Rack Storage System
The dataset is used for training and testing the DAD:DeepAnomalyDetection algorithm. It contains observations from a hybrid production system, including continuous and discrete... -
Memory-Augmented Deep Autoencoder for Unsupervised Anomaly Detection
Memory-Augmented Deep Autoencoder for Unsupervised Anomaly Detection -
Isolation Forest
Isolation Forest -
Long Short Term Memory Networks for Anomaly Detection in Time Series
Long Short Term Memory Networks for Anomaly Detection in Time Series
