A review of research works on supervised learning algorithms for SCADA intrusion detection and classification
Supervisory Control and Data Acquisition (SCADA) systems play a significant role in
providing remote access, monitoring and control of critical infrastructures (CIs) which …
providing remote access, monitoring and control of critical infrastructures (CIs) which …
Deep learning and computer vision will transform entomology
Most animal species on Earth are insects, and recent reports suggest that their abundance is
in drastic decline. Although these reports come from a wide range of insect taxa and regions …
in drastic decline. Although these reports come from a wide range of insect taxa and regions …
Video anomaly detection with spatio-temporal dissociation
Anomaly detection in videos remains a challenging task due to the ambiguous definition of
anomaly and the complexity of visual scenes from real video data. Different from the …
anomaly and the complexity of visual scenes from real video data. Different from the …
Generative Adversarial Networks for Anomaly Detection in Medical Images
B Vyas, RM Rajendran - … and Research Methodology, ISSN: 2960-2068, 2023 - ijmirm.com
In computer vision, anomaly detection (AD) is a challenging task. AD presents additional
difficulties, especially in the realm of medical imaging, for several reasons, one of which …
difficulties, especially in the realm of medical imaging, for several reasons, one of which …
Contrastive autoencoder for anomaly detection in multivariate time series
H Zhou, K Yu, X Zhang, G Wu, A Yazidi - Information Sciences, 2022 - Elsevier
With the proliferation of the Internet of Things, a large amount of multivariate time series
(MTS) data is being produced daily by industrial systems, corresponding in many cases to …
(MTS) data is being produced daily by industrial systems, corresponding in many cases to …
Deep anomaly detection with self-supervised learning and adversarial training
Deep anomaly detection, which utilizes neural networks to discover anomalies, is a vital
research topic in pattern recognition. With the burgeoning of inference mechanism …
research topic in pattern recognition. With the burgeoning of inference mechanism …
FL-MGVN: Federated learning for anomaly detection using mixed gaussian variational self-encoding network
D Wu, Y Deng, M Li - Information processing & management, 2022 - Elsevier
Anomalous data are such data that deviate from a large number of normal data points, which
often have negative impacts on various systems. Current anomaly detection technology …
often have negative impacts on various systems. Current anomaly detection technology …
Anomaly detection using improved deep SVDD model with data structure preservation
Z Zhang, X Deng - Pattern Recognition Letters, 2021 - Elsevier
Support vector data description (SVDD) is a classical anomaly detection algorithm. How to
develop a deep version of SVDD is one valuable problem in the anomaly detection field …
develop a deep version of SVDD is one valuable problem in the anomaly detection field …
[HTML][HTML] From beasts to bytes: Revolutionizing zoological research with artificial intelligence
Since the late 2010s, Artificial Intelligence (AI) including machine learning, boosted through
deep learning, has boomed as a vital tool to leverage computer vision, natural language …
deep learning, has boomed as a vital tool to leverage computer vision, natural language …
READ-IoT: reliable event and anomaly detection framework for the Internet of Things
A Yahyaoui, T Abdellatif, S Yangui, R Attia - IEEE Access, 2021 - ieeexplore.ieee.org
Internet of Things (IoT) enables a myriad of applications by interconnecting software to
physical objects. The objects range from wireless sensors to robots and include surveillance …
physical objects. The objects range from wireless sensors to robots and include surveillance …