Deep learning for anomaly detection: A review
Anomaly detection, aka outlier detection or novelty detection, has been a lasting yet active
research area in various research communities for several decades. There are still some …
research area in various research communities for several decades. There are still some …
Deep learning for anomaly detection: A survey
Anomaly detection is an important problem that has been well-studied within diverse
research areas and application domains. The aim of this survey is two-fold, firstly we present …
research areas and application domains. The aim of this survey is two-fold, firstly we present …
COVID-19 cough classification using machine learning and global smartphone recordings
We present a machine learning based COVID-19 cough classifier which can discriminate
COVID-19 positive coughs from both COVID-19 negative and healthy coughs recorded on a …
COVID-19 positive coughs from both COVID-19 negative and healthy coughs recorded on a …
Description and discussion on DCASE2020 challenge task2: Unsupervised anomalous sound detection for machine condition monitoring
In this paper, we present the task description and discuss the results of the DCASE 2020
Challenge Task 2: Unsupervised Detection of Anomalous Sounds for Machine Condition …
Challenge Task 2: Unsupervised Detection of Anomalous Sounds for Machine Condition …
[PDF][PDF] Deep learning for unsupervised insider threat detection in structured cybersecurity data streams
Abstract Analysis of an organization's computer network activity is a key component of early
detection and mitigation of insider threat, a growing concern for many organizations. Raw …
detection and mitigation of insider threat, a growing concern for many organizations. Raw …
Collective anomaly detection based on long short-term memory recurrent neural networks
Intrusion detection for computer network systems is becoming one of the most critical tasks
for network administrators today. It has an important role for organizations, governments and …
for network administrators today. It has an important role for organizations, governments and …
Anomalous sound detection based on interpolation deep neural network
As the labor force decreases, the demand for labor-saving automatic anomalous sound
detection technology that conducts maintenance of industrial equipment has grown …
detection technology that conducts maintenance of industrial equipment has grown …
Unsupervised detection of anomalous sound based on deep learning and the neyman–pearson lemma
Y Koizumi, S Saito, H Uematsu… - … on Audio, Speech …, 2018 - ieeexplore.ieee.org
This paper proposes a novel optimization principle and its implementation for unsupervised
anomaly detection in sound (ADS) using an autoencoder (AE). The goal of the unsupervised …
anomaly detection in sound (ADS) using an autoencoder (AE). The goal of the unsupervised …
GeoTrackNet—A Maritime Anomaly Detector Using Probabilistic Neural Network Representation of AIS Tracks and A Contrario Detection
D Nguyen, R Vadaine, G Hajduch… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Representing maritime traffic patterns and detecting anomalies from them are key to vessel
monitoring and maritime situational awareness. We propose a novel approach—referred to …
monitoring and maritime situational awareness. We propose a novel approach—referred to …
An ensemble of prediction and learning mechanism for improving accuracy of anomaly detection in network intrusion environments
The connectivity of our surrounding objects to the internet plays a tremendous role in our
daily lives. Many network applications have been developed in every domain of life …
daily lives. Many network applications have been developed in every domain of life …