This paper presents a strategy to improve the AdaBoost algorithm with a quadratic combination of base classifiers. We observe that learning this combination is necessary to get be...
Classifying network flows by their application type is the backbone of many crucial network monitoring and controlling tasks, including billing, quality of service, security and tr...
Roni Bar-Yanai, Michael Langberg, David Peleg, Lia...
This paper addresses the issue of the explanation of the result given to the end-user by a classifier, when it is used as a decision support system. We consider machine learning cl...
This paper presents reliable techniques for detecting, tracking, and storing keyframes of people in surveillance video. The first component of our system is a novel face detector ...
Online Boosting is an effective incremental learning method which can update weak classifiers efficiently according to the object being trackedt. It is a promising technique for o...