A new boosting algorithm ADABOOST-R for regression problems is presented and upper bound on the error is obtained. Experimental results to compare ADABOOST-R and other learning alg...
In this paper, we propose a cascaded version of the online boosting algorithm to speed-up the execution time and guarantee real-time performance even when employing a large number ...
Ingrid Visentini, Lauro Snidaro, Gian Luca Foresti
A new strategy is proposed for the design of cascaded object detectors of high detection-rate. The problem of jointly minimizing the false-positive rate and classification complex...
We tackle the problem of automatically classifying cardiac view for an echocardiographic sequence as a multiclass object detection. As a solution, we present an imagebased multicl...
Shaohua Kevin Zhou, J. H. Park, Bogdan Georgescu, ...
We propose to use AdaBoost to efficiently learn classifiers over very large and possibly distributed data sets that cannot fit into main memory, as well as on-line learning wher...