SOTAVerified

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

Papers

Showing 17261750 of 4856 papers

TitleStatusHype
Hi-SAM: A high-scalable authentication model for satellite-ground Zero-Trust system using mean field game0
A Methodological Report on Anomaly Detection on Dynamic Knowledge Graphs0
Anomaly Detection in Time Series of EDFA Pump Currents to Monitor Degeneration Processes using Fuzzy Clustering0
What Matters in Autonomous Driving Anomaly Detection: A Weakly Supervised HorizonCode0
Audio-visual cross-modality knowledge transfer for machine learning-based in-situ monitoring in laser additive manufacturing0
Adversarially Robust Industrial Anomaly Detection Through Diffusion Model0
Performance Metric for Multiple Anomaly Score Distributions with Discrete Severity LevelsCode0
Hybrid Efficient Unsupervised Anomaly Detection for Early Pandemic Case Identification0
Cross-Domain Learning for Video Anomaly Detection with Limited Supervision0
The Role and Applications of Airport Digital Twin in Cyberattack Protection during the Generative AI Era0
Generating Fine-Grained Causality in Climate Time Series Data for Forecasting and Anomaly Detection0
FedAD-Bench: A Unified Benchmark for Federated Unsupervised Anomaly Detection in Tabular Data0
Anomaly Prediction: A Novel Approach with Explicit Delay and Horizon0
Towards High-resolution 3D Anomaly Detection via Group-Level Feature Contrastive LearningCode0
Cluster-Wide Task Slowdown Detection in Cloud SystemCode0
Self-Supervised Contrastive Graph Clustering Network via Structural Information Fusion0
Dual-Modeling Decouple Distillation for Unsupervised Anomaly Detection0
Unsupervised Detection of Fetal Brain Anomalies using Denoising Diffusion Models0
Online Model-based Anomaly Detection in Multivariate Time Series: Taxonomy, Survey, Research Challenges and Future Directions0
Online Electric Vehicle Charging Detection Based on Memory-based Transformer using Smart Meter Data0
CKNN: Cleansed k-Nearest Neighbor for Unsupervised Video Anomaly DetectionCode0
Can LLMs Serve As Time Series Anomaly Detectors?0
A Classifier-Based Approach to Multi-Class Anomaly Detection Applied to Astronomical Time-SeriesCode0
Operational range bounding of spectroscopy models with anomaly detection0
AssemAI: Interpretable Image-Based Anomaly Detection for Manufacturing PipelinesCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CPR-faster(TensorRT)FPS1,016Unverified
2CPR-fast(TensorRT)FPS362Unverified
3CPR(TensorRT)FPS130Unverified
4GLASSDetection AUROC99.9Unverified
5UniNetDetection AUROC99.9Unverified
6HETMMDetection AUROC99.8Unverified
7INP-Fomer ViT-L (model-unified multi-class)Detection AUROC99.8Unverified
8EfficientAD (early stopping)Detection AUROC99.8Unverified
9DDADDetection AUROC99.8Unverified
10PBASDetection AUROC99.8Unverified
#ModelMetricClaimedVerifiedStatus
1UniNetDetection AUROC99.8Unverified
2GLADDetection AUROC99.5Unverified
3UniNet(model-unified multi-class)Detection AUROC99.15Unverified
4INP-Former ViT-B (model-unified multi-class)Detection AUROC98.9Unverified
5DDADDetection AUROC98.9Unverified
6Dinomaly ViT-L (model-unified multi-class)Detection AUROC98.9Unverified
7DiffusionADDetection AUROC98.8Unverified
8GLASSDetection AUROC98.8Unverified
9TransFusionDetection AUROC98.7Unverified
10HETMMDetection AUROC98.1Unverified
#ModelMetricClaimedVerifiedStatus
1CSADAvg. Detection AUROC95.3Unverified
2PSADAvg. Detection AUROC94.9Unverified