168 Open source projects that are alternatives of or similar to ADRepository-Anomaly-detection-datasets

A scikit-learn compatible library for anomaly detection

Supplementary material for KDD 2018 workshop "DCSO: Dynamic Combination of Detector Scores for Outlier Ensembles"

Supplementary material for IJCNN paper "XGBOD: Improving Supervised Outlier Detection with Unsupervised Representation Learning"

(Python, R, C++) Explainable outlier/anomaly detection through decision tree conditioning

Source code of the KDD19 paper "Deep anomaly detection with deviation networks", weakly/partially supervised anomaly detection, few-shot anomaly detection

Code for reproducing f-AnoGAN in Pytorch

TOD: GPU-accelerated Outlier Detection via Tensor Operations

Main component extraction for outlier detection

Official PyTorch implementation of the paper “Explainable Deep Few-shot Anomaly Detection with Deviation Networks”, weakly/partially supervised anomaly detection, few-shot anomaly detection, image defect detection.

A Deep Graph-based Toolbox for Fraud Detection in TensorFlow 2.X

Anomaly detection related books, papers, videos, and toolboxes

A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)

List of tools & datasets for anomaly detection on time-series data.

Official pytorch implementation of the paper: "A Hierarchical Transformation-Discriminating Generative Model for Few Shot Anomaly Detection"

anomaly detection with anomalize and Google Trends data

Example of Anomaly Detection using Convolutional Variational Auto-Encoder (CVAE)

The collection of pre-trained, state-of-the-art AI models for ailia SDK

benfordslaw is about the frequency distribution of leading digits.

MemStream: Memory-Based Streaming Anomaly Detection

基于智能计算框架nupic的异常检测restful Api.

Code for 'Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images' [MICCAI 2021]

DDC-Outlier: Preventing medication errors using unsupervised learning

Interactive Visualization to Build, Train and Test an Autoencoder with Tensorflow.js

anomaly detection by one-class SVM

An R package for space-time anomaly detection using scan statistics.

Digital Cell Sorter (DCS): single cell RNA-seq analysis toolkit. Documentation:

https://events.kaspersky.com/hackathon/

No description or website provided.

PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation (CVPR 2021)

Implementation of the famous Image Manipulation\Forgery Detector "ManTraNet" in Pytorch

A quick and dirty vehicle speed detector using video + anomaly detection

Implementation of TheWebConf 2021 -- Few-shot Network Anomaly Detection via Cross-network Meta-learning

Detection of Accounting Anomalies in the Latent Space using Adversarial Autoencoder Neural Networks - A lab we prepared for the KDD'19 Workshop on Anomaly Detection in Finance that will walk you through the detection of interpretable accounting anomalies using adversarial autoencoder neural networks. The majority of the lab content is based on J…

A repository for code accompanying the manuscript 'An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series' (published at TNNLS)

Sherlock is an anomaly detection service built on top of Druid

Mean-Shifted Contrastive Loss for Anomaly Detection

Library for multi-dimensional, multi-sensor, uni/multivariate time series data analysis, unsupervised feature selection, unsupervised deep anomaly detection, and prototype of explainable AI for anomaly detector

Resources for working with time series and sequence data

IPCCC 2018: Robust and Unsupervised KPI Anomaly Detection Based on Conditional Variational Autoencoder

Official source code of "Fast Adaptive RNN Encoder-Decoder for Anomaly Detection in SMD Assembly Machine"

Industrial knn-based anomaly detection for images. Visit streamlit link to check out the demo.

VisualQC : assistive tool to ease the quality control workflow of neuroimaging data.

The Combined Anomalous Object Segmentation (CAOS) Benchmark

⭐ An anomaly-based intrusion detection system.

A parallel implementation of local outlier factor based on Spark

The Kubervisor allow you to control which pods should receive traffic or not based on anomaly detection.It is a new kind of health check system.

Feature Space Singularity for Out-of-Distribution Detection. (SafeAI 2021)

[ti]ny [li]ttle machine learning [tool]box - Machine learning, anomaly detection, one-class classification, and structured output prediction

Deploying a Batch Scoring Pipeline for Python Models

This is the code for the paper nemed 'Anomaly Detection for Hyperspectral Imagery Based on the Regularized Subspace Method and Collaborative Representation'

Solve many kinds of least-squares and matrix-recovery problems

Official code for 'Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning' [ICCV 2021]

some anomaly detection models and experiments.

Implementation of feature engineering from Feature engineering strategies for credit card fraud

Python toolbox for transfer learning.

A Ground Mobile Robot Perception Dataset, IEEE RA-L & IEEE T-CYB

Threat Detection & Anomaly Detection rules for popular open-source components

Repository for detecting outliers using Grubb's Threshold & Generalized Extreme Studentized Deviate (ESD) Test

A Python library for anomaly detection

The Ultimate Reference for Out of Distribution Detection with Deep Neural Networks