A unifying review of deep and shallow anomaly detection

L Ruff, JR Kauffmann, RA Vandermeulen… - Proceedings of the …, 2021 - ieeexplore.ieee.org
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 …

An overview of online fake news: Characterization, detection, and discussion

X Zhang, AA Ghorbani - Information Processing & Management, 2020 - Elsevier
Over the recent years, the growth of online social media has greatly facilitated the way
people communicate with each other. Users of online social media share information …

Widespread global increase in intense lake phytoplankton blooms since the 1980s

JC Ho, AM Michalak, N Pahlevan - Nature, 2019 - nature.com
Freshwater blooms of phytoplankton affect public health and ecosystem services globally,.
Harmful effects of such blooms occur when the intensity of a bloom is too high, or when toxin …

Hyperspectral anomaly detection: A survey

H Su, Z Wu, H Zhang, Q Du - IEEE Geoscience and Remote …, 2021 - ieeexplore.ieee.org
Hyperspectral imagery can obtain hundreds of narrow spectral bands of ground objects. The
abundant and detailed spectral information offers a unique diagnostic identification ability for …

The Burden of Proof studies: assessing the evidence of risk

P Zheng, A Afshin, S Biryukov, C Bisignano, M Brauer… - Nature Medicine, 2022 - nature.com
Exposure to risks throughout life results in a wide variety of outcomes. Objectively judging
the relative impact of these risks on personal and population health is fundamental to …

A review of local outlier factor algorithms for outlier detection in big data streams

O Alghushairy, R Alsini, T Soule, X Ma - Big Data and Cognitive …, 2020 - mdpi.com
Outlier detection is a statistical procedure that aims to find suspicious events or items that
are different from the normal form of a dataset. It has drawn considerable interest in the field …

Data fusion and machine learning for industrial prognosis: Trends and perspectives towards Industry 4.0

A Diez-Olivan, J Del Ser, D Galar, B Sierra - Information Fusion, 2019 - Elsevier
The so-called “smartization” of manufacturing industries has been conceived as the fourth
industrial revolution or Industry 4.0, a paradigm shift propelled by the upsurge and …

Construction of the average variance extracted index for construct validation in structural equation models with adaptive regressions

PM dos Santos, MÂ Cirillo - Communications in Statistics …, 2023 - Taylor & Francis
A range of indicators, such as the average variance extracted (AVE), is commonly used to
validate constructs. In statistics, AVE is a measure of the amount of variance that is captured …

Artificial intelligence (AI) in augmented reality (AR)-assisted manufacturing applications: a review

CK Sahu, C Young, R Rai - International Journal of Production …, 2021 - Taylor & Francis
Augmented reality (AR) has proven to be an invaluable interactive medium to reduce
cognitive load by bridging the gap between the task-at-hand and relevant information by …

Revisiting time series outlier detection: Definitions and benchmarks

KH Lai, D Zha, J Xu, Y Zhao, G Wang… - Thirty-fifth conference on …, 2021 - openreview.net
Time series outlier detection has been extensively studied with many advanced algorithms
proposed in the past decade. Despite these efforts, very few studies have investigated how …