Abstract. We present a method that improves the results of network intrusion detection by integration of several anomaly detection algorithms through trust and reputation models. O...
In this paper, we propose a novel solution for multi-view object detection. Given a set of training examples at different views, we select examples at a few key views and train on...
We introduce a generalized representation for a boosted classifier with multiple exit nodes, and propose a method to training which combines the idea of propagating scores across ...
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...
In this paper, we propose a powerful symmetric radial basis function (RBF) classifier for nonlinear detection in the so-called "overloaded" multiple-antenna-aided communi...
Sheng Chen, Andreas Wolfgang, Chris J. Harris, Laj...