171 Open source projects that are alternatives of or similar to traffic

Anomaly detection using LoOP: Local Outlier Probabilities, a local density based outlier detection method providing an outlier score in the range of [0,1].

Open-source framework to detect outliers in Elasticsearch events

Python toolbox for transfer learning.

We have used Deep Reinforcement Learning and Advanced Computer Vision techniques to for the creation of Smart Traffic Signals for Indian Roads. We have created the scripts for using SUMO as our environment for deploying all our RL models.

A PyTorch implementation of Deep SAD, a deep Semi-supervised Anomaly Detection method.

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.

Anomaly detection analysis and labeling tool, specifically for multiple time series (one time series per category)

anomaly detection by one-class SVM

Repository for the Deep One-Class Classification ICML 2018 paper

A scikit-learn compatible library for anomaly detection

Massively real-time traffic streaming application

A Python 3 library making time series data mining tasks, utilizing matrix profile algorithms, accessible to everyone.

Code for reproducing f-AnoGAN in Pytorch

Monitor ethernet traffic in real time with a 3D backend.

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

The fundamental package for AIops with python.

some anomaly detection models and experiments.

Go implementation of MIDAS: Microcluster-Based Detector of Anomalies in Edge Streams

Gets in the way of your victim's traffic and out of yours

Isolation Forest on Spark

A Python library for anomaly detection

Unsupervised anomaly detection with generative model, keras implementation

No description or website provided.

Latent space autoregression for novelty detection.

An open source real-time network topology and protocols analyzer

The code of the Object Counting API, implemented with the YOLO algorithm and with the SORT algorithm

An End-to-end Outlier Detection System

TOD: GPU-accelerated Outlier Detection via Tensor Operations

No description or website provided.

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

[ACM MM 2020] Uncertainty-based Traffic Accident Anticipation

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

(MLSys' 21) An Acceleration System for Large-scare Unsupervised Heterogeneous Outlier Detection (Anomaly Detection)

Data pipeline project

Anomaly detection library based on singular spectrum transformation(sst)

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

Unofficial Tensorflow Implementation of AnoGAN (Anomaly GAN)

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

Pytorch Implementation of DeepLog.

Main component extraction for outlier detection

Anomaly detection for temporal data using LSTMs

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.

Log Anomaly Detection - Machine learning to detect abnormal events logs

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

Hastic data management server for labeling patterns and anomalies in Grafana

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

R package for automation of machine learning, forecasting, feature engineering, model evaluation, model interpretation, data generation, and recommenders.

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

KitNET is a lightweight online anomaly detection algorithm, which uses an ensemble of autoencoders.

Sherlock is an anomaly detection service built on top of Druid

Anomaly detection for streaming time series, featuring automated model selection.

Open Source Deep Packet Inspection Software Toolkit

STUMPY is a powerful and scalable Python library for modern time series analysis

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…

Rack middleware to send traffic logs to Fluentd

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

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]

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

Android network connection blocker and packet analyzer built on top of local HTTP proxy.