Machine learning for anomaly detection: A systematic review
Anomaly detection has been used for decades to identify and extract anomalous
components from data. Many techniques have been used to detect anomalies. One of the …
components from data. Many techniques have been used to detect anomalies. One of the …
Anomaly detection in earth dam and levee passive seismic data using support vector machines and automatic feature selection
We investigate techniques for earth dam and levee health monitoring and automatic
detection of anomalous events in passive seismic data. We have developed a novel data …
detection of anomalous events in passive seismic data. We have developed a novel data …
Detection and segmentation of cement concrete pavement pothole based on image processing technology
M Gao, X Wang, S Zhu, P Guan - Mathematical Problems in …, 2020 - Wiley Online Library
Potholes are the most common form of distress on cement concrete pavements, which can
compromise pavement safety and ridability. Thus, timely and accurate pothole detection is …
compromise pavement safety and ridability. Thus, timely and accurate pothole detection is …
An efficient and robust unsupervised anomaly detection method using ensemble random projection in surveillance videos
Video anomaly detection is widely applied in modern society, which is achieved by sensors
such as surveillance cameras. This paper learns anomalies by exploiting videos under the …
such as surveillance cameras. This paper learns anomalies by exploiting videos under the …
Early detection of internal erosion in earth dams: combining seismic monitoring and convolutional AutoEncoders
N Yousefpour, FF Mojtahedi - … of Risk for Engineered Systems and …, 2024 - Taylor & Francis
Levees/earth dams are critical infrastructures for supplementing clean water, flood
management, and energy production, prone to progressive failures due to internal erosion …
management, and energy production, prone to progressive failures due to internal erosion …
Earth orientation parameters prediction based on the hybrid SSA+ LS+ SVM model
Y Yang, W Nie, T Xu, Z Fang, H Xue… - … Science and Technology, 2022 - iopscience.iop.org
The high-precision prediction of Earth orientation parameters (EOPs) is essential for astro-
geodynamics, high-precision space navigation and positioning, on-board autonomous orbits …
geodynamics, high-precision space navigation and positioning, on-board autonomous orbits …
Performance and membrane fouling behaviors analysis with SVR-LibSVM model in a submerged anaerobic membrane bioreactor treating low-strength domestic …
J Liu, X Kang, X Luan, L Gao, H Tian, X Liu - Environmental Technology & …, 2020 - Elsevier
A submerged anaerobic membrane bioreactor (SAnMBR) was operated for low-strength
domestic sewage treatment over a period of 190 days. Average chemical oxygen demand …
domestic sewage treatment over a period of 190 days. Average chemical oxygen demand …
Anomaly detection of policies in distributed firewalls using data log analysis
A Andalib, SM Babamir - The Journal of Supercomputing, 2023 - Springer
A distributed firewall is a security application that monitors and controls traffic on an
organization's network. While centralized firewalls are used against attacks coming from …
organization's network. While centralized firewalls are used against attacks coming from …
Using weighted extreme learning machine combined with scale-invariant feature transform to predict protein-protein interactions from protein evolutionary information
Protein-Protein Interactions (PPIs) play an irreplaceable role in biological activities of
organisms. Although many high-throughput methods are used to identify PPIs from different …
organisms. Although many high-throughput methods are used to identify PPIs from different …
Diagnosis of multiple sclerosis from EEG signals using nonlinear methods
A Torabi, MR Daliri, SH Sabzposhan - Australasian physical & …, 2017 - Springer
EEG signals have essential and important information about the brain and neural diseases.
The main purpose of this study is classifying two groups of healthy volunteers and Multiple …
The main purpose of this study is classifying two groups of healthy volunteers and Multiple …