Adaptive tracking-by-detection methods are widely used in computer vision for tracking arbitrary objects. Current approaches treat the tracking problem as a classification task a...
Abstract. This paper proposes a generic extension to propositional rule learners to handle multiple-instance data. In a multiple-instance representation, each learning example is r...
Modern classification applications necessitate supplementing the few available labeled examples with unlabeled examples to improve classification performance. We present a new tra...
In this paper, the problem of estimating the damping factor and frequency parameters from multiple cisoids in noise is addressed. We rst propose a data matrix which generalizes th...
In this paper, we propose a novel framework called SmartMiner for web usage mining problem which uses link information for producing accurate user sessions and frequent navigation...
Murat Ali Bayir, Ismail Hakki Toroslu, Ahmet Cosar...