Browsing by Subject "Anomaly Detection"
Now showing items 1-8 of 8
-
(2022-12-09)Anomaly detection, which aims to identify unusual or uncommon behaviors in data, has many real-world applications. While numerous machine learning algorithms have been developed for anomaly detection, we often still need ...
-
(2021-10-22)Identifying anomalies with complex patterns is different from the conventional anomaly detection problem. Firstly, for cross-modal anomaly detection problems, a large portion of data instances within a multi-modal context ...
-
(2021-05-03)There is no world without energy. Dependence on energy continues to dominate everything that we do. It is known that any failure in the production of energy can directly affect thousands of lives. Because of this, data is ...
-
(2021-12-01)Material from CSCE 704 Data Analytics for Cybersecurity taught by Dr. Martin Carlisle is made available here as part of the National Science Foundation (NSF) grant (award number 1730695)- CyberTraining: CIP: CiSE-ProS: ...
-
(2019-06-12)The electric power grid uses a set of measuring and switching devices for its operations and control. The data retrieved from the measuring instruments is assumed to be noisy, therefore a state estimator is used to estimate ...
-
Previously many studies have aimed at predicting the trend of a disease through time series forecasting using machine learning methods. However, data extracted from the real world is often noisy, which can pose numerous ...
-
(2017-12-09)Critical infrastructures such as power grids, water treatment and distribution facilities, and Building Automation Systems (BAS) have come to employ Cyber-Physical Systems (CPSs) in which physical devices or components are ...
-
(2020-06-09)Anomaly detection techniques are supposed to identify anomalies from loads of seemingly homogeneous data and being able to do so can lead us to timely, pivotal and actionable decisions, saving us from potential human, ...