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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://github.com/mazurowski-lab/picard

공식 코드

Unsupervised anomaly localization in high-resolution breast scans using deep pluralistic image completion

https://github.com/mbohlkeschneider/gluon-ts

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High-Dimensional Multivariate Forecasting with Low-Rank Gaussian Copula Processes

https://github.com/mdabashar/TAnoGAN

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TAnoGAN: Time Series Anomaly Detection with Generative Adversarial Networks

https://github.com/mdivyanshu97/discovr

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Self-supervised Learning of Echocardiographic Video Representations via Online Cluster Distillation

https://github.com/medaitech/scrd4ad

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Scale-Aware Contrastive Reverse Distillation for Unsupervised Medical Anomaly Detection

https://github.com/mediabrain-sjtu/ecgad

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Multi-scale Cross-restoration Framework for Electrocardiogram Anomaly Detection

https://github.com/mediabrain-sjtu/mvfa-ad

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Adapting Visual-Language Models for Generalizable Anomaly Detection in Medical Images

https://github.com/mediabrain-sjtu/regad

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Registration based Few-Shot Anomaly Detection

https://github.com/meghanathmacha/xPACS

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Explaining Anomalies in Groups with Characterizing Subspace Rules

https://github.com/meilfang/spl-mad

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Unsupervised Face Morphing Attack Detection via Self-paced Anomaly Detection

https://github.com/mengchillee/gen2out

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gen2Out: Detecting and Ranking Generalized Anomalies

https://github.com/mengjiezhao/dyedgegat

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DyEdgeGAT: Dynamic Edge via Graph Attention for Early Fault Detection in IIoT Systems

https://github.com/mesarcik/nln

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Improving Novelty Detection using the Reconstructions of Nearest Neighbours

https://github.com/mesarcik/road

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The ROAD to discovery: machine learning-driven anomaly detection in radio astronomy spectrograms

https://github.com/meteor0033/high-pass_gad

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High-Pass Graph Convolutional Network for Enhanced Anomaly Detection: A Novel Approach

https://github.com/mhkim9714/MIXAD

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MIXAD: Memory-Induced Explainable Time Series Anomaly Detection

https://github.com/mi3labucm/coooler

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Towards a Multi-Agent Vision-Language System for Zero-Shot Novel Hazardous Object Detection for Autonomous Driving Safety

https://github.com/miccunifi/tape

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Reference-based Restoration of Digitized Analog Videotapes

https://github.com/michaelneri/image-based-network-traffic-anomaly-detection

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Unsupervised Network Anomaly Detection with Autoencoders and Traffic Images

https://github.com/michaelneri/unsupervised-audio-anomaly-detection

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Low-complexity Attention-based Unsupervised Anomalous Sound Detection exploiting Separable Convolutions and Angular Loss

https://github.com/miirho3ein/real_time_bhm

공식 코드

Exploring Scalable, Distributed Real-Time Anomaly Detection for Bridge Health Monitoring

https://github.com/mikelasz/flipad

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Single-Model Attribution of Generative Models Through Final-Layer Inversion

https://github.com/mikemccabe210/mapper_comparison

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Mapper Comparison with Wasserstein Metrics

https://github.com/mila-iqia/cableinspect-ad-code

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CableInspect-AD: An Expert-Annotated Anomaly Detection Dataset

https://github.com/mile888/anomaly_identification

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Power System Anomaly Detection and Classification Utilizing WLS-EKF State Estimation and Machine Learning

https://github.com/milestonesys-research/vad-with-pgms

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Bounding Boxes and Probabilistic Graphical Models: Video Anomaly Detection Simplified

https://github.com/mims-harvard/UniTS

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UniTS: A Unified Multi-Task Time Series Model

https://github.com/minh-nghia/AE-1SVM

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Scalable and Interpretable One-class SVMs with Deep Learning and Random Fourier features

https://github.com/minjiyoon/anomrank

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Fast and Accurate Anomaly Detection in Dynamic Graphs with a Two-Pronged Approach

https://github.com/minkiml/NFM

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Neural Fourier Modelling: A Highly Compact Approach to Time-Series Analysis

https://github.com/minqi824/adbench

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ADBench: Anomaly Detection Benchmark

https://github.com/minqi824/adgym

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ADGym: Design Choices for Deep Anomaly Detection

https://github.com/minqi824/overlap

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Anomaly Detection with Score Distribution Discrimination

https://github.com/mirqr/fedad

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Anomaly Detection through Unsupervised Federated Learning

https://github.com/missinghwan/MSAD

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Label-based Graph Augmentation with Metapath for Graph Anomaly Detection

https://github.com/missinghwan/anomix

공식 코드

ANOMIX: A Simple yet Effective Hard Negative Generation via Mixing for Graph Anomaly Detection

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