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Spot-the-difference
Spot-the-difference self-supervised pre-training for anomaly detection and segmentation. -
DMAD: Dual Memory Bank for Real-World Anomaly Detection
Training a unified model is considered to be more suitable for practical industrial anomaly detection scenarios due to its generalization ability and storage efficiency.... -
Rotating Machine Dataset
Vibration sensor data from five rotating machines -
NASA IMS Bearing Dataset
Vibration sensor data from four bearings -
Federated Learning for Autoencoder-based Condition Monitoring in the Industri...
Two real-world datasets for condition monitoring and anomaly detection in rotating machines -
ISCXTor2016
The dataset used in this paper for anomaly multimedia traffic identification in graynet. -
KDD Cup 1999 Dataset
The KDD Cup 1999 dataset contains a set of instances that represent connections to a military computer network. -
KDDCUP99 dataset
The dataset used in this paper is the KDDCUP99 dataset, which contains network traffic data from a military network. -
UCSD dataset
The UCSD dataset is a benchmark for the analysis of abnormal detection and localization in crowded scenes. -
Custom Carpet Dataset
A custom dataset of four unique types of carpet textures was created to thoroughly test state-of-the-art unsupervised detection models. -
LANL dataset
The LANL dataset consists of over one billion log lines collected over 58 consecutive days. The logs contain anonymized process, network flow, DNS, and authentication information. -
Shuttle Dataset
The shuttle dataset is used for anomaly clustering and visualization. It contains 9 numerical attributes and 7 classes. -
SWaT and WADI datasets
The dataset is used for multivariate anomaly detection on time series data generated by cyber-physical systems. -
Anomaly Detection in Cyber-Physical Systems
The dataset is used for anomaly detection in cyber-physical systems.