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https://www.researchgate.net/publication/224200478_Using_support_vector_machines_for_anomalous_change_detection
We cast anomalous change detection as a binary classification problem, and use a support vector machine (SVM) to build a detector that does not depend on …
http://geodesy.unr.edu/hanspeterplag/library/IGARSS2010/pdfs/1453.pdf
USING SUPPORT VECTOR MACHINES FOR ANOMALOUS CHANGE DETECTION Ingo Steinwart, James Theiler, and Daniel Llamocca Los Alamos National Laboratory Los Alamos, NM 87545 1. INTRODUCTION Given two images of the same scene, taken at different times and (inevitably) under different conditions, we consider the problem of nding anomalous changes …
https://www.researchgate.net/profile/Gl_Foresti/publication/232636648_Anomalous_trajectory_detection_using_support_vector_machines/links/55cdf95908ae6a881381b101.pdf
ANOMALOUS TRAJECTORY DETECTION USING SUPPORT VECTOR MACHINES C. Piciarelli, G. L. Foresti Department of Mathematics and Computer Science University of UdineCited by: 16
https://www.osti.gov/servlets/purl/1022064
We cast anomalous change detection as a binary classification problem, and use a support vector machine (SVM) to build a detector that does not depend on assumptions about the underlying data distribution. To speed up the computation, our SVM is implemented, in part, on a graphical processing unit ...
http://www.cs.unc.edu/~jeffay/courses/nidsS05/ai/robust-anomaly-detection-using.pdf
Robust Anomaly Detection Using Support Vector Machines Wenjie Hu Yihua Liao V. Rao Vemuri Department of Applied Science Department of Computer Science Department of Applied Science University of California, Davis University of California, Davis University of California, Davis [email protected] [email protected] [email protected]
http://www2.stat.duke.edu/~kheller/ocsvmpr.pdf
One Class Support Vector Machines for Detecting Anomalous Windows Registry Accesses Katherine A. Heller Krysta M. Svore Angelos D. Keromytis Salvatore J. Stolfo Dept. of Computer Science Columbia University 1214 Amsterdam Avenue New York, NY 10025 heller,kmsvore,angelos,sal @cs.columbia.edu Abstract We present a new Host-based …
https://www.cs.drexel.edu/~salvucci/publications/Mandalia-HFES05.pdf
USING SUPPORT VECTOR MACHINES FOR LANE-CHANGE DETECTION Hiren M. Mandalia Dario D. Salvucci Drexel University Drexel University Philadelphia, PA Philadelphia, PA Driving is a complex task that requires constant attention, and intelligent transportation systems that
https://link.springer.com/article/10.1007/s11063-015-9457-y
Jul 11, 2015 · Hence, in this letter, we proposed a new classifier to improve the anomalous attacks detection rate based on support vector machine (SVM) and genetic programming (GP). Based on the experimental results, our classifier, GPSVM, managed to get higher detection rate on the anomalous rare attacks, without significant reduction on the overall accuracy.Cited by: 10
https://www.osti.gov/pages/biblio/1213439
We cast anomalous change detection as a binary classification problem, and use a support vector machine (SVM) to build a detector that does not depend on assumptions about the underlying data distribution. To speed up the computation, our SVM is implemented, in part, on a graphical processing unit.
https://www.sciencedirect.com/science/article/pii/S1877750316304185
Our research thus far proves internal erosion events are separable in earth dam and levee (EDL) passive seismic data using unsupervised clustering and crack detection using support vector machines . In this paper, we continue development of an automatic anomaly detection scheme.Cited by: 25
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