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Anomaly Detection

104 papers with code · Methodology

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Latest papers with code

ToyADMOS: A Dataset of Miniature-Machine Operating Sounds for Anomalous Sound Detection

9 Aug 2019YumaKoizumi/ToyADMOS-dataset

To build a large-scale dataset for ADMOS, we collected anomalous operating sounds of miniature machines (toys) by deliberately damaging them.

ANOMALY DETECTION

10
09 Aug 2019

MSNM-S: An Applied Network Monitoring Tool for Anomaly Detection in Complex Networks and Systems

31 Jul 2019nesg-ugr/msnm-sensor

This way, new solutions to monitor and detect security events are needed addressing new challenges coming from this scenario that are, among others, the number of devices to monitor, the huge amount of data to manage and the real time requirement to provide a quick security event detection and, consequently, quick attack reaction.

ANOMALY DETECTION

6
31 Jul 2019

Self-Attentive, Multi-Context One-Class Classification for Unsupervised Anomaly Detection on Text

ACL 2019 lukasruff/CVDD-PyTorch

There exist few text-specific methods for unsupervised anomaly detection, and for those that do exist, none utilize pre-trained models for distributed vector representations of words.

UNSUPERVISED ANOMALY DETECTION

3
01 Jul 2019

GluonTS: Probabilistic Time Series Models in Python

12 Jun 2019awslabs/gluon-ts

We introduce Gluon Time Series (GluonTS, available at https://gluon-ts. mxnet. io), a library for deep-learning-based time series modeling.

ANOMALY DETECTION TIME SERIES TIME SERIES FORECASTING TIME SERIES PREDICTION

581
12 Jun 2019

Deep Semi-Supervised Anomaly Detection

6 Jun 2019lukasruff/Deep-SAD-PyTorch

Deep approaches to anomaly detection have recently shown promising results over shallow approaches on high-dimensional data.

ANOMALY DETECTION

12
06 Jun 2019

ManTra-Net: Manipulation Tracing Network for Detection and Localization of Image Forgeries With Anomalous Features

CVPR 2019 ISICV/ManTraNet

To fight against real-life image forgery, which commonly involves different types and combined manipulations, we propose a unified deep neural architecture called ManTra-Net.

ANOMALY DETECTION

17
01 Jun 2019

Unsupervised Learning of Anomaly Detection from Contaminated Image Data using Simultaneous Encoder Training

27 May 2019amandaberg/GANanomalyDetection

In this work, we examine the effects of contaminating training data with anomalies for state-of-the-art GAN-based anomaly detection methods.

ANOMALY DETECTION

2
27 May 2019

The Machine Learning Bazaar: Harnessing the ML Ecosystem for Effective System Development

22 May 2019HDI-Project/AutoBazaar

To address these problems, we introduce the Machine Learning Bazaar, a new approach to developing machine learning and automated machine learning software systems.

ANOMALY DETECTION AUTOML GRAPH MATCHING

5
22 May 2019

Attack and Anomaly Detection in IoT Sensors in IoT Sites Using Machine Learning Approaches

journal 2019 Shauqi/Attack-and-Anomaly-Detection-in-IoT-Sensors-in-IoT-Sites-Using-Machine-Learning-Approaches

The machine learning (ML) algorithms that have been used here are Logistic Regression (LR), Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), and Artificial Neural Network (ANN).

ANOMALY DETECTION

0
11 May 2019

Functional Isolation Forest

9 Apr 2019Gstaerman/FIF

For the purpose of monitoring the behavior of complex infrastructures (e. g. aircrafts, transport or energy networks), high-rate sensors are deployed to capture multivariate data, generally unlabeled, in quasi continuous-time to detect quickly the occurrence of anomalies that may jeopardize the smooth operation of the system of interest.

ANOMALY DETECTION

6
09 Apr 2019