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» Automatic feature selection for anomaly detection
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KDD
2009
ACM
232views Data Mining» more  KDD 2009»
15 years 10 months ago
Classification of software behaviors for failure detection: a discriminative pattern mining approach
Software is a ubiquitous component of our daily life. We often depend on the correct working of software systems. Due to the difficulty and complexity of software systems, bugs an...
David Lo, Hong Cheng, Jiawei Han, Siau-Cheng Khoo,...
85
Voted
IJIT
2004
14 years 11 months ago
Morphing Human Faces: Automatic Control Points Selection And Color Transition
In this paper, we propose a morphing method by which face color images can be freely transformed. The main focus of this work is the transformation of one face image to another. Th...
Stephen Karungaru, Minoru Fukumi, Norio Akamatsu
ICASSP
2011
IEEE
14 years 1 months ago
Detection of anomalous events from unlabeled sensor data in smart building environments
This paper presents a robust unsupervised learning approach for detection of anomalies in patterns of human behavior using multi-modal smart environment sensor data. We model the ...
Padmini Jaikumar, Aca Gacic, Burton Andrews, Micha...
AMI
2009
Springer
15 years 4 months ago
Behavior Analysis Based on Coordinates of Body Tags
This paper describes fall detection, activity recognition and the detection of anomalous gait in the Confidence project. The project aims to prolong the independence of the elderly...
Mitja Lustrek, Bostjan Kaluza, Erik Dovgan, Bogdan...
KDD
2004
ACM
126views Data Mining» more  KDD 2004»
15 years 10 months ago
Selection, combination, and evaluation of effective software sensors for detecting abnormal computer usage
We present and empirically analyze a machine-learning approach for detecting intrusions on individual computers. Our Winnowbased algorithm continually monitors user and system beh...
Jude W. Shavlik, Mark Shavlik