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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 4551–4575 of 4856 papers

TitleStatusHype
Federated Learning-Driven Cybersecurity Framework for IoT Networks with Privacy-Preserving and Real-Time Threat Detection Capabilities—0
Federated Learning for Anomaly Detection in Energy Consumption Data: Assessing the Vulnerability to Adversarial Attacks—0
Federated Learning for Distributed Spectrum Sensing in NextG Communication Networks—0
Federated Learning for Efficient Condition Monitoring and Anomaly Detection in Industrial Cyber-Physical Systems—0
Federated Learning for Intrusion Detection System: Concepts, Challenges and Future Directions—0
Federated Learning framework for LoRaWAN-enabled IIoT communication: A case study—0
Federated Semi-Supervised Classification of Multimedia Flows for 3D Networks—0
Federated Structured Sparse PCA for Anomaly Detection in IoT Networks—0
Federated Variational Learning for Anomaly Detection in Multivariate Time Series—0
Feedforward Neural Network for Time Series Anomaly Detection—0
FEMa-FS: Finite Element Machines for Feature Selection—0
Fence Theorem: Preprocessing is Dual-Objective Semantic Structure Isolator in 3D Anomaly Detection—0
FetalFlex: Anatomy-Guided Diffusion Model for Flexible Control on Fetal Ultrasound Image Synthesis—0
Few-shot Anomaly Detection in Text with Deviation Learning—0
Few-Shot Anomaly Detection with Adversarial Loss for Robust Feature Representations—0
Few-Shot Bearing Fault Diagnosis Based on Model-Agnostic Meta-Learning—0
Cross-System Categorization of Abnormal Traces in Microservice-Based Systems via Meta-Learning—0
Deep Representation Learning with an Information-theoretic Loss—0
Few-Shot Defect Segmentation Leveraging Abundant Normal Training Samples Through Normal Background Regularization and Crop-and-Paste Operation—0
Few-shot Detection of Anomalies in Industrial Cyber-Physical System via Prototypical Network and Contrastive Learning—0
Few-shot Message-Enhanced Contrastive Learning for Graph Anomaly Detection—0
Few-shot time-series anomaly detection with unsupervised domain adaptation—0
Few-shot Weakly-supervised Cybersecurity Anomaly Detection—0
FGAD: Self-boosted Knowledge Distillation for An Effective Federated Graph Anomaly Detection Framework—0
FGAN: Federated Generative Adversarial Networks for Anomaly Detection in Network Traffic—0
Show:102550
← PrevPage 183 of 195Next →
All datasetsMVTec ADVisAMVTec LOCO ADOne-class CIFAR-10CUHK AvenueShanghaiTechFishyscapes L&FUCR Anomaly ArchiveMPDDBTADOne-class CIFAR-100UBnormal

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CPR-faster(TensorRT)FPS1,016—Unverified
2CPR-fast(TensorRT)FPS362—Unverified
3CPR(TensorRT)FPS130—Unverified
4GLASSDetection AUROC99.9—Unverified
5UniNetDetection AUROC99.9—Unverified
6HETMMDetection AUROC99.8—Unverified
7INP-Fomer ViT-L (model-unified multi-class)Detection AUROC99.8—Unverified
8EfficientAD (early stopping)Detection AUROC99.8—Unverified
9DDADDetection AUROC99.8—Unverified
10PBASDetection AUROC99.8—Unverified
#ModelMetricClaimedVerifiedStatus
1UniNetDetection AUROC99.8—Unverified
2GLADDetection AUROC99.5—Unverified
3UniNet(model-unified multi-class)Detection AUROC99.15—Unverified
4INP-Former ViT-B (model-unified multi-class)Detection AUROC98.9—Unverified
5DDADDetection AUROC98.9—Unverified
6Dinomaly ViT-L (model-unified multi-class)Detection AUROC98.9—Unverified
7DiffusionADDetection AUROC98.8—Unverified
8GLASSDetection AUROC98.8—Unverified
9TransFusionDetection AUROC98.7—Unverified
10HETMMDetection AUROC98.1—Unverified
#ModelMetricClaimedVerifiedStatus
1CSADAvg. Detection AUROC95.3—Unverified
2PSADAvg. Detection AUROC94.9—Unverified