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 …
Modeling, diagnostics, optimization, and control of internal combustion engines via modern machine learning techniques: A review and future directions
A critical review of the existing Internal Combustion Engine (ICE) modeling, optimization,
diagnosis, and control challenges and the promising state-of-the-art Machine Learning (ML) …
diagnosis, and control challenges and the promising state-of-the-art Machine Learning (ML) …
[HTML][HTML] Gaia data release 3-summary of the content and survey properties
A Vallenari, AGA Brown, T Prusti… - Astronomy & …, 2023 - aanda.org
Context. We present the third data release of the European Space Agency's Gaia mission,
Gaia DR3. This release includes a large variety of new data products, notably a much …
Gaia DR3. This release includes a large variety of new data products, notably a much …
[HTML][HTML] Accelerated western European heatwave trends linked to more-persistent double jets over Eurasia
Persistent heat extremes can have severe impacts on ecosystems and societies, including
excess mortality, wildfires, and harvest failures. Here we identify Europe as a heatwave …
excess mortality, wildfires, and harvest failures. Here we identify Europe as a heatwave …
Rethinking semantic segmentation: A prototype view
Prevalent semantic segmentation solutions, despite their different network designs (FCN
based or attention based) and mask decoding strategies (parametric softmax based or pixel …
based or attention based) and mask decoding strategies (parametric softmax based or pixel …
[HTML][HTML] A survey on semi-supervised learning
JE Van Engelen, HH Hoos - Machine learning, 2020 - Springer
Semi-supervised learning is the branch of machine learning concerned with using labelled
as well as unlabelled data to perform certain learning tasks. Conceptually situated between …
as well as unlabelled data to perform certain learning tasks. Conceptually situated between …
Gaia Data Release 3-Astrophysical parameters inference system (Apsis). I. Methods and content overview
OL Creevey, R Sordo, F Pailler, Y Frémat… - Astronomy & …, 2023 - aanda.org
Gaia Data Release 3 contains a wealth of new data products for the community.
Astrophysical parameters are a major component of this release, and were produced by the …
Astrophysical parameters are a major component of this release, and were produced by the …
Benchmarking of machine learning for anomaly based intrusion detection systems in the CICIDS2017 dataset
An intrusion detection system (IDS) is an important protection instrument for detecting
complex network attacks. Various machine learning (ML) or deep learning (DL) algorithms …
complex network attacks. Various machine learning (ML) or deep learning (DL) algorithms …
[HTML][HTML] Recent advances and applications of machine learning in solid-state materials science
One of the most exciting tools that have entered the material science toolbox in recent years
is machine learning. This collection of statistical methods has already proved to be capable …
is machine learning. This collection of statistical methods has already proved to be capable …
Machine learning for reliability engineering and safety applications: Review of current status and future opportunities
Abstract Machine learning (ML) pervades an increasing number of academic disciplines and
industries. Its impact is profound, and several fields have been fundamentally altered by it …
industries. Its impact is profound, and several fields have been fundamentally altered by it …