Boosting-basedmethods have recently led to the state-ofthe-art face detection systems. In these systems, weak classifiers to be boosted are based on simple, local, Haar-like featu...
Though AdaBoost has been widely used for feature selection and classifier learning, many of the selected features, or weak classifiers, are redundant. By incorporating mutual infor...
LinLin Shen, Li Bai, Daniel Bardsley, Yangsheng Wa...
The selection of weak classifiers is critical to the success of boosting techniques. Poor weak classifiers do not perform better than random guess, thus cannot help decrease the t...
Abstract. In the present article a framework for the robust detection of mobile robots using nested cascades of boosted classifiers is proposed. The boosted classifiers are trained...
We consider the existence of a linear weak learner for boosting algorithms. A weak learner for binary classification problems is required to achieve a weighted empirical error on t...