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

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Showing 2801–2850 of 4856 papers

TitleStatusHype
Explainable multi-class anomaly detection on functional data—0
Object Class Aware Video Anomaly Detection through Image Translation—0
Multimodal Detection of Unknown Objects on Roads for Autonomous DrivingCode1
TracInAD: Measuring Influence for Anomaly DetectionCode0
ARCADE: Adversarially Regularized Convolutional Autoencoder for Network Anomaly Detection—0
ADDAI: Anomaly Detection using Distributed AI—0
MemSeg: A semi-supervised method for image surface defect detection using differences and commonalitiesCode2
Federated Semi-Supervised Classification of Multimedia Flows for 3D Networks—0
Abnormal-aware Multi-person Evaluation System with Improved Fuzzy Weighting—0
Unseen Anomaly Detection on Networks via Multi-Hypersphere LearningCode0
Anomaly Detection by Leveraging Incomplete Anomalous Knowledge with Anomaly-Aware Bidirectional GANsCode1
Meta-Learning Based Early Fault Detection for Rolling Bearings via Few-Shot Anomaly Detection—0
IRC-safe Graph Autoencoder for unsupervised anomaly detection—0
Novel Applications for VAE-based Anomaly Detection Systems—0
Topological Data Analysis for Anomaly Detection in Host-Based Logs—0
A Survey on Unsupervised Anomaly Detection Algorithms for Industrial Images—0
GFCL: A GRU-based Federated Continual Learning Framework against Data Poisoning Attacks in IoV—0
Discriminative Feature Learning Framework with Gradient Preference for Anomaly Detection—0
NLP Based Anomaly Detection for Categorical Time Series—0
Hybrid Cloud-Edge Collaborative Data Anomaly Detection in Industrial Sensor Networks—0
Feature anomaly detection system (FADS) for intelligent manufacturing—0
A Revealing Large-Scale Evaluation of Unsupervised Anomaly Detection AlgorithmsCode1
Representation Learning for Content-Sensitive Anomaly Detection in Industrial NetworksCode1
Delamination prediction in composite panels using unsupervised-feature learning methods with wavelet-enhanced guided wave representations—0
Multi-Component Optimization and Efficient Deployment of Neural-Networks on Resource-Constrained IoT HardwareCode1
Scalable Motif Counting for Large-scale Temporal GraphsCode0
Robustness Testing of Data and Knowledge Driven Anomaly Detection in Cyber-Physical Systems—0
Sintel: A Machine Learning Framework to Extract Insights from SignalsCode3
"Flux+Mutability": A Conditional Generative Approach to One-Class Classification and Anomaly Detection—0
Multi-scale Anomaly Detection for Big Time Series of Industrial Sensors—0
AI for human assessment: What do professional assessors need?—0
AFSC: Adaptive Fourier Space Compression for Anomaly Detection—0
Anomalous Sound Detection Based on Machine Activity Detection—0
LSTM-Autoencoder based Anomaly Detection for Indoor Air Quality Time Series DataCode1
Self-Supervised Losses for One-Class Textual Anomaly Detection—0
Unsupervised Anomaly and Change Detection with Multivariate Gaussianization—0
Unsupervised Anomaly Detection in 3D Brain MRI using Deep Learning with impured training data—0
EPASAD: Ellipsoid decision boundary based Process-Aware Stealthy Attack Detector—0
A Video Anomaly Detection Framework based on Appearance-Motion Semantics Representation Consistency—0
Adversarial Machine Learning Attacks Against Video Anomaly Detection Systems—0
Federated Learning for Distributed Spectrum Sensing in NextG Communication Networks—0
Learning to Adapt to Domain Shifts with Few-shot Samples in Anomalous Sound Detection—0
A Survey on Graph Representation Learning Methods—0
Distributed Anomaly Detection and Estimation over Sensor Networks: Observational-Equivalence and Q-Redundant Observer Design—0
Do Deep Neural Networks Contribute to Multivariate Time Series Anomaly Detection?—0
SAM-kNN Regressor for Online Learning in Water Distribution NetworksCode0
Proactive Anomaly Detection for Robot Navigation with Multi-Sensor FusionCode1
Quadratic Neuron-empowered Heterogeneous Autoencoder for Unsupervised Anomaly DetectionCode0
LEAD1.0: A Large-scale Annotated Dataset for Energy Anomaly Detection in Commercial BuildingsCode1
IGRF-RFE: A Hybrid Feature Selection Method for MLP-based Network Intrusion Detection on UNSW-NB15 Dataset—0
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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