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
R Chalapathy, S Chawla - arXiv preprint arXiv:1901.03407, 2019 - arxiv.org
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
L Bontemps, VL Cao, J McDermott… - Future Data and Security …, 2016 - Springer
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 …