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Normal vs. Abnormal Behavior

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dc.contributor.authorJensen, Aprileng
dc.contributor.authorGavrilova, Marinaeng
dc.date.accessioned2008-02-26T20:33:12Z
dc.date.available2008-02-26T20:33:12Z
dc.date.computerscience2006-02-15eng
dc.date.issued2006-02-15eng
dc.description.abstractThe term outlier refers to data that deviates significantly from what is considered normal. Outliers are often of interest since they may indicate that data was generated by a mechanism other than the expected one [23], or may indicate abnormal or suspicious behavior. The modeling and analysis of normal vs. abnormal behavior proves useful in security-related areas such as biometrics, video surveillance and intrusion-detection, as well as in other areas such as medical imaging, among others.eng
dc.description.notesWe are currently acquiring citations for the work deposited into this collection. We recognize the distribution rights of this item may have been assigned to another entity, other than the author(s) of the work.If you can provide the citation for this work or you think you own the distribution rights to this work please contact the Institutional Repository Administrator at digitize@ucalgary.caeng
dc.identifier.department2006-819-12eng
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/30618
dc.identifier.urihttp://hdl.handle.net/1880/45489
dc.language.isoEngeng
dc.publisher.corporateUniversity of Calgaryeng
dc.publisher.facultyScienceeng
dc.subjectComputer Scienceeng
dc.titleNormal vs. Abnormal Behavioreng
dc.typeunknown
thesis.degree.disciplineComputer Scienceeng

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