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 4201–4250 of 4856 papers

TitleStatusHype
Defending Water Treatment Networks: Exploiting Spatio-temporal Effects for Cyber Attack Detection—0
Defending Against Adversarial Denial-of-Service Data Poisoning Attacks—0
Degradation Prediction of Semiconductor Lasers using Conditional Variational Autoencoder—0
Delamination prediction in composite panels using unsupervised-feature learning methods with wavelet-enhanced guided wave representations—0
Demo: A Digital Twin of the 5G Radio Access Network for Anomaly Detection Functionality—0
Demonstrating the Suitability of Neuromorphic, Event-Based, Dynamic Vision Sensors for In Process Monitoring of Metallic Additive Manufacturing and Welding—0
Dense Out-of-Distribution Detection by Robust Learning on Synthetic Negative Data—0
Dens-PU: PU Learning with Density-Based Positive Labeled Augmentation—0
Dependency-based Anomaly Detection: a General Framework and Comprehensive Evaluation—0
Design of a dynamic and self adapting system, supported with artificial intelligence, machine learning and real time intelligence for predictive cyber risk analytics in extreme environments, cyber risk in the colonisation of Mars—0
DETECTA 2.0: Research into non-intrusive methodologies supported by Industry 4.0 enabling technologies for predictive and cyber-secure maintenance in SMEs—0
Detecting abnormal events in video using Narrowed Normality Clusters—0
Detecting abnormalities in resting-state dynamics: An unsupervised learning approach—0
Detecting Anomalies from Video-Sequences: a Novel Descriptor—0
Detecting Anomalies in Blockchain Transactions using Machine Learning Classifiers and Explainability Analysis—0
Detecting Anomalies Through Contrast in Heterogeneous Data—0
Detecting Anomalies using Generative Adversarial Networks on Images—0
Detecting Anomalies Using Rotated Isolation Forest—0
Detecting Anomalous Cryptocurrency Transactions: an AML/CFT Application of Machine Learning-based Forensics—0
Detecting Anomalous Invoice Line Items in the Legal Case Lifecycle—0
Detecting Anomalous User Behavior in Remote Patient Monitoring—0
Detecting Anomaly in Chemical Sensors via L1-Kernels based Principal Component Analysis—0
Detecting Attacks on IoT Devices using Featureless 1D-CNN—0
Detecting Backdoors in Neural Networks Using Novel Feature-Based Anomaly Detection—0
Detecting Clusters of Anomalies on Low-Dimensional Feature Subsets with Application to Network Traffic Flow Data—0
Detecting Compromised IoT Devices Using Autoencoders with Sequential Hypothesis Testing—0
Detecting Contextual Anomalies by Discovering Consistent Spatial Regions—0
Detecting Contextual Network Anomalies with Graph Neural Networks—0
Detecting Crypto Pump-and-Dump Schemes: A Thresholding-Based Approach to Handling Market Noise—0
Detecting Cyberattacks in Industrial Control Systems Using Convolutional Neural Networks—0
Detecting Disengagement in Virtual Learning as an Anomaly using Temporal Convolutional Network Autoencoder—0
Detecting Driver Drowsiness as an Anomaly Using LSTM Autoencoders—0
EVBattery: A Large-Scale Electric Vehicle Dataset for Battery Health and Capacity Estimation—0
Detecting fake accounts through Generative Adversarial Network in online social media—0
Detecting Faults during Automatic Screwdriving: A Dataset and Use Case of Anomaly Detection for Automatic Screwdriving—0
Detecting Financial Market Manipulation with Statistical Physics Tools—0
Detecting Gait Abnormalities in Foot-Floor Contacts During Walking Through Footstep-Induced Structural Vibrations—0
Detecting Log Anomalies with Multi-Head Attention (LAMA)—0
Detecting Novelties with Empty Classes—0
Detecting out-of-context objects using contextual cues—0
Detecting Out-Of-Distribution Earth Observation Images with Diffusion Models—0
Detecting Out-of-distribution Samples via Variational Auto-encoder with Reliable Uncertainty Estimation—0
Detecting Point Outliers Using Prune-based Outlier Factor (PLOF)—0
Detecting Relative Anomaly—0
Detecting Spelling and Grammatical Anomalies in Russian Poetry Texts—0
Detecting subtle cyberattacks on adaptive cruise control vehicles: A machine learning approach—0
Power-Grid Controller Anomaly Detection with Enhanced Temporal Deep Learning—0
Detection and Analysis of Drive-by-Download Attacks and Malicious JavaScript Code—0
Detection and Statistical Modeling of Birth-Death Anomaly—0
D\'etection automatique d'anomalies sur deux styles de parole dysarthrique: parole lue vs spontan\'ee (Automatic anomaly detection for dysarthria across two speech styles : read vs spontaneous speech)—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