A unifying review of deep and shallow anomaly detection
Deep learning approaches to anomaly detection (AD) have recently improved the state of
the art in detection performance on complex data sets, such as large collections of images or …
the art in detection performance on complex data sets, such as large collections of images or …
Review of fall detection techniques: A data availability perspective
A fall is an abnormal activity that occurs rarely; however, missing to identify falls can have
serious health and safety implications on an individual. Due to the rarity of occurrence of …
serious health and safety implications on an individual. Due to the rarity of occurrence of …
MIMII Dataset: Sound dataset for malfunctioning industrial machine investigation and inspection
Factory machinery is prone to failure or breakdown, resulting in significant expenses for
companies. Hence, there is a rising interest in machine monitoring using different sensors …
companies. Hence, there is a rising interest in machine monitoring using different sensors …
DCASE 2017 challenge setup: Tasks, datasets and baseline system
DCASE 2017 Challenge consists of four tasks: acoustic scene classification, detection of
rare sound events, sound event detection in real-life audio, and large-scale weakly …
rare sound events, sound event detection in real-life audio, and large-scale weakly …
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 …
Machine learning for the detection and identification of Internet of Things devices: A survey
The Internet of Things (IoT) is becoming an indispensable part of everyday life, enabling a
variety of emerging services and applications. However, the presence of rogue IoT devices …
variety of emerging services and applications. However, the presence of rogue IoT devices …
[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 …
Detection and classification of acoustic scenes and events: Outcome of the DCASE 2016 challenge
Public evaluation campaigns and datasets promote active development in target research
areas, allowing direct comparison of algorithms. The second edition of the challenge on …
areas, allowing direct comparison of algorithms. The second edition of the challenge on …
Autoencoders and their applications in machine learning: a survey
Autoencoders have become a hot researched topic in unsupervised learning due to their
ability to learn data features and act as a dimensionality reduction method. With rapid …
ability to learn data features and act as a dimensionality reduction method. With rapid …
ToyADMOS: A dataset of miniature-machine operating sounds for anomalous sound detection
This paper introduces a new dataset called" ToyADMOS" designed for anomaly detection in
machine operating sounds (ADMOS). To the best our knowledge, no large-scale datasets …
machine operating sounds (ADMOS). To the best our knowledge, no large-scale datasets …