Hyperspectral imaging is highly important with respect to the detection, identification and
classification of various natural resources—minerals, earth's natural eruptions, vegetation …

Anomaly detection of industrial control systems (ICS) based on sensor data analytic is of
utmost importance because ICS may suffer from various attacks leading to anomaly …

Supervised Learning (SL) celebrates a lot of research topics in machine learning (ML) and
provides a large number of applications in multimedia. The effectiveness and performance …

Recently, One-class classification algorithms have been successfully used for outlier
detection problems in several industrial fields. However, in case of that the target class has …

Abstract Anomaly detection of Industrial Control Systems (ICS) plays a crucial role in
ensuring system safety and improving product quality. However, traditional anomaly …

Abstract Machine learning (ML) is an approach driven by data, and as research in machine
learning progresses, the issue of noisy labels has garnered widespread attention. Noisy …

Abstract Rough-Fuzzy Support Vector Data Description is a novel soft computing derivative
of the classical Support Vector Data Description algorithm used in many real-world …

Undertaking anomaly detection on turnout with missing fault data shows an important role in
ensuring railway safety. In this paper, the kernel alignment technique is used to calculate the …