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Anomaly Detection

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하위 태스크: 28
평가표: 76
보존된 평가 기록: 669

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

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://bitbucket.org/maciekwielgosz/anomaly_detection

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The model of an anomaly detector for HiLumi LHC magnets based on Recurrent Neural Networks and adaptive quantization

https://bitbucket.org/papers_vad_group/vision_to_sound_ad

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From Vision to Sound: Advancing Audio Anomaly Detection with Vision-Based Algorithms

https://bitbucket.org/tinyad24/paste-sup

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PaSTe: Improving the Efficiency of Visual Anomaly Detection at the Edge

https://github.com/13952522076/incrementalad

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Online Self-Evolving Anomaly Detection in Cloud Computing Environments

https://github.com/17000cyh/imdiffusion

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ImDiffusion: Imputed Diffusion Models for Multivariate Time Series Anomaly Detection

https://github.com/22strongestme/LOCO-Annotations

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LogiCode: an LLM-Driven Framework for Logical Anomaly Detection

https://github.com/98chao/ProtoAD

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A Prototype-Based Neural Network for Image Anomaly Detection and Localization

https://github.com/99eren99/dirfiaf

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Deep Image Restoration For Image Anti-Forensics

https://github.com/99eren99/dis25k

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Deep Image Composition Meets Image Forgery

https://github.com/AIRS-CSR/FractalAD

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FractalAD: A simple industrial anomaly detection method using fractal anomaly generation and backbone knowledge distillation

https://github.com/AMD-RIPS/ST-2019

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Automating Artifact Detection in Video Games

https://github.com/APILASTRI/DCASE_Task2_UMINHO

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Deep Dense and Convolutional Autoencoders for Unsupervised Anomaly Detection in Machine Condition Sounds

https://github.com/ARM-software/ML-zoo

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MicroNets: Neural Network Architectures for Deploying TinyML Applications on Commodity Microcontrollers

https://github.com/ARhaman/EGANs-vs.GMM

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Enhanced anomaly detection in well log data through the application of ensemble GANs

https://github.com/AbertayMachineLearningGroup/network-threats-taxonomy

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A Taxonomy of Network Threats and the Effect of Current Datasets on Intrusion Detection Systems

https://github.com/AhmedFrikha/ARCADe-A-Rapid-Continual-Anomaly-Detector

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ARCADe: A Rapid Continual Anomaly Detector

https://github.com/AhmedFrikha/Few-Shot-One-Class-Classification-via-Meta-Learning

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Few-Shot One-Class Classification via Meta-Learning

https://github.com/AlbertoBarbado/unsupervised-outlier-transparency

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Rule Extraction in Unsupervised Anomaly Detection for Model Explainability: Application to OneClass SVM

https://github.com/Alrash/TimesURL

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TimesURL: Self-supervised Contrastive Learning for Universal Time Series Representation Learning

https://github.com/AmitRozner/Anomaly-Detection-with-Variance-Stabilized-Density-Estimation

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Anomaly Detection with Variance Stabilized Density Estimation

https://github.com/AmmarKamoona/Multiple-Instance-Based-Video-Anomaly-Detection-Using-Deep-Temporal-Encoding-Decoding

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Multiple Instance-Based Video Anomaly Detection using Deep Temporal Encoding-Decoding

https://github.com/AmmarKamoona/RFS-Energy-Anomaly-Detection-of-Defect

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Anomaly Detection of Defect using Energy of Point Pattern Features within Random Finite Set Framework

https://github.com/AndreyAgeev/Attention-based-isolation-forest

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Improved Anomaly Detection by Using the Attention-Based Isolation Forest

https://github.com/Anfeather/CMG

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Improving Vision Anomaly Detection with the Guidance of Language Modality

https://github.com/AnthonyDeschenes/PlaningItByEarDataset

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Planing It by Ear: Convolutional Neural Networks for Acoustic Anomaly Detection in Industrial Wood Planers

https://github.com/Armanfard-Lab/DASVDD

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DASVDD: Deep Autoencoding Support Vector Data Descriptor for Anomaly Detection

https://github.com/AslantheAslan/beta-GNN

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$β$-GNN: A Robust Ensemble Approach Against Graph Structure Perturbation

https://github.com/Au3C2/Generator-Versus-Segmentor

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Generator Versus Segmentor: Pseudo-healthy Synthesis

https://github.com/Azure/mmlspark

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Large-Scale Intelligent Microservices

https://github.com/BenedictWilkinsAI/S3N

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A Metric Learning Approach to Anomaly Detection in Video Games

https://github.com/BinhangYuan/WaveletFCNN

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WaveletAE: A Wavelet-enhanced Autoencoder for Wind Turbine Blade Icing Detection

https://github.com/CIOL-SUST/SCG

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Graph Neural Networks in Supply Chain Analytics and Optimization: Concepts, Perspectives, Dataset and Benchmarks

https://github.com/CN-TU/tpsdos-experiments

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SDOoop: Capturing Periodical Patterns and Out-of-phase Anomalies in Streaming Data Analysis

https://github.com/CV-Lehigh/Bias_IMD

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Exploring Saliency Bias in Manipulation Detection

https://github.com/Choubo/deviation-network-image

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Explainable Deep Few-shot Anomaly Detection with Deviation Networks

https://github.com/ChunjingXiao/CAGAD

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Counterfactual Data Augmentation with Denoising Diffusion for Graph Anomaly Detection

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.