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ISMIS
2005
Springer
14 years 29 days ago
Learning the Daily Model of Network Traffic
Abstract. Anomaly detection is based on profiles that represent normal behaviour of users, hosts or networks and detects attacks as significant deviations from these profiles. In t...
Costantina Caruso, Donato Malerba, Davide Papagni
ICPR
2004
IEEE
14 years 8 months ago
Detecting Abnormal Regions in Colonoscopic Images by Patch-based Classifier Ensemble
In this paper, a new method is proposed to detect abnormal regions in colonoscopic images by patch-based classifier ensemble. Through supervised learning from image patches of var...
Kap Luk Chan, Peng Li, Shankar Muthu Krishnan, Yan...
ICCV
2005
IEEE
14 years 9 months ago
Probabilistic Boosting-Tree: Learning Discriminative Models for Classification, Recognition, and Clustering
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Zhuowen Tu
CVPR
2011
IEEE
13 years 4 months ago
Repetition-based Dense Single-View Reconstruction
This paper presents a novel approach for dense reconstruction from a single-view of a repetitive scene structure. Given an image and its detected repetition regions, we model the ...
Changchang Wu, Jan-Michael Frahm, Marc Pollefeys
ICC
2007
IEEE
14 years 1 months ago
A Novel k-Parent Flooding Tree for Secure and Reliable Broadcasting in Sensor Networks
Abstract— Securing broadcast communication over sensor networks is an important research challenge. In general, broadcast communication has two important metrics: security and re...
Avinash Srinivasan, Jie Wu