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» Anomaly Detection Using Visualization and Machine Learning
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ANSS
2006
IEEE
15 years 4 months ago
USim: A User Behavior Simulation Framework for Training and Testing IDSes in GUI Based Systems
Anomaly detection systems largely depend on user profile data to be able to detect deviation from normal activity. Most of this profile data is based on commands executed by use...
Ashish Garg, Vidyaraman Sankaranarayanan, Shambhu ...
LREC
2008
140views Education» more  LREC 2008»
14 years 11 months ago
Toward Active Learning in Data Selection: Automatic Discovery of Language Features During Elicitation
Data Selection has emerged as a common issue in language technologies. We define Data Selection as the choosing of a subset of training data that is most effective for a given tas...
Jonathan Clark, Robert E. Frederking, Lori S. Levi...
ICML
2000
IEEE
15 years 10 months ago
Hierarchical Unsupervised Learning
We consider the problem of unsupervised classification of temporal sequences of facial expressions in video. This problem arises in the design of an adaptive visual agent, which m...
Shivakumar Vaithyanathan, Byron Dom
ICMCS
2007
IEEE
133views Multimedia» more  ICMCS 2007»
15 years 4 months ago
Data Modeling Strategies for Imbalanced Learning in Visual Search
In this paper we examine a novel approach to the difficult problem of querying video databases using visual topics with few examples. Typically with visual topics, the examples a...
Jelena Tesic, Apostol Natsev, Lexing Xie, John R. ...
PAMI
2008
302views more  PAMI 2008»
14 years 10 months ago
Learning to Detect Moving Shadows in Dynamic Environments
We propose a novel adaptive technique for detecting moving shadows and distinguishing them from moving objects in video sequences. Most methods for detecting shadows work in a stat...
Ajay J. Joshi, Nikolaos Papanikolopoulos