Results 201 to 210 of about 20,582 (244)

Spatially divided outlier removal for LiDAR de-noising in adverse weather conditions. [PDF]

Sci Rep
Shin S, Joo J, Lee H, Kim SC.
europepmc   +1 more source

Quantifying and Improving Stereo Camera Calibration Robustness: An Outlier-Aware Algorithm for Digital Twin Data Acquisition. [PDF]

J Imaging
Carbureanu M, Zamfir FS.
europepmc   +1 more source

Quality-Controlled Generative Augmentation for North Atlantic Right Whale Upcall Detection Using Contour 1D-VAE. [PDF]

Sensors (Basel)
Ahn J, Park GH, Bae HS, Lee D.
europepmc   +1 more source

AudioUnlock: Device-to-Device Authentication via Acoustic Signatures and One-Class Classifiers. [PDF]

Sensors (Basel)
Anistoroaei A, Iosif P, Burlacu C, Berdich A, Groza B.   +4 more
europepmc   +1 more source

A High-Fidelity Multi-Model Benchmark Dataset for General Aviation Anomaly Detection Generated via Physics-Based Fault Injection. [PDF]

Sci Data
Lu J, Fang Y, Huang Z, Zhang Y, Fan S, Wu X.   +5 more
europepmc   +1 more source

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GMBLOF: A Machine Learning Algorithm of Novelty Detection Based on Local Outlier Factor

2022 5th International Conference on Pattern Recognition and Artificial Intelligence (PRAI), 2022
Pan Huang, Peng Feng
exaly   +2 more sources

Distributed filtering algorithm based on local outlier factor under data integrity attacks

Journal of the Franklin Institute, 2023
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yue Luo, Yun Liu 0015, Wen Yang 0002, Jiayu Zhou, Taolin Lv   +4 more
openaire   +1 more source

A Genetic-Based Incremental Local Outlier Factor Algorithm for Efficient Data Stream Processing

Proceedings of the 2020 4th International Conference on Compute and Data Analysis, 2020
Interest in outlier detection methods is increasing because detecting outliers is an important operation for many applications such as detecting fraud transactions in credit card, network intrusion detection and data analysis in different domains. We are now in the big data era, and an important type of big data is data stream.
Omar Alghushairy, Raed Alsini, Xiaogang Ma 0001, Terence Soule   +3 more
openaire   +1 more source

Accelerating the local outlier factor algorithm on a GPU for intrusion detection systems

Proceedings of the 3rd Workshop on General-Purpose Computation on Graphics Processing Units, 2010
The Local Outlier Factor (LOF) is a very powerful anomaly detection method available in machine learning and classification. The algorithm defines the notion of local outlier in which the degree to which an object is outlying is dependent on the density of its local neighborhood, and each object can be assigned an LOF which represents the likelihood of
Malak Alshawabkeh, Byunghyun Jang, David R. Kaeli   +2 more
openaire   +2 more sources

A Comparative Study of Local Outlier Factor Algorithms for Outliers Detection in Data Streams

2018
Outlier detection analyzes data, finds out anomalies, and helps to discover unforeseen activities in safety crucial systems. Outlier detection helps in early prediction of various fraudulent activities like credit card theft, fake insurance claim, tax stealing, real-time monitoring, medical systems, online transactions, and many more.
Supriya Mishra, Meenu Chawla
openaire   +1 more source