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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.... -
Paper-Author
Paper-Author: This dataset contains papers crawled from the arXiv preprint database. Nodes U represent papers, while nodes V represent authors. An edge ⟨u, v⟩ indicates that the... -
Moving Metric Detection and Alerting System at eBay
eBay product health metrics for different domain teams to monitor -
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 -
Clinical Brain CT Scans
Clinical brain CT scans dataset used for anomaly detection in brain CT scans -
IoT testbed dataset
The IoT testbed dataset contains data from various IoT devices under different attack conditions. -
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. -
Robust Anomaly Detection for Multivariate Time Series
Robust anomaly detection for multivariate time series through stochastic recurrent neural network. -
KDDCUP99 dataset
The dataset used in this paper is the KDDCUP99 dataset, which contains network traffic data from a military network. -
FAIR: Frequency-aware Image Restoration for Industrial Visual Anomaly Detection
Image reconstruction-based anomaly detection models are widely explored in industrial visual inspection. However, existing models usually suffer from the trade-off between... -
Remote Patient Monitoring (RPM) dataset
Remote Patient Monitoring (RPM) dataset, containing data from smart health devices and home sensors. -
SeMAnD: Self-Supervised Anomaly Detection in Multimodal Geospatial Datasets
Geospatial datasets are diverse, naturally spatiotemporal, and inherently multimodal (composed of two or more distinct signal types or modalities) e.g., satellite/aerial imagery... -
Time series forecasting to detect anomalous behaviours in Multiphase Flow Meters
Time series forecasting to detect anomalous behaviours in Multiphase Flow Meters