This paper addresses the initial shift problem in iterative learning control with system relative degree. The tracking error caused by nonzero initial shift is detected when apply...
Usually, object detection is performed directly on (normalized) gray values or gray primitives like gradients or Haar-like features. In that case the learning of relationships bet...
Jeroen Lichtenauer, Emile A. Hendriks, Marcel J. T...
AdaBoost is a well known, effective technique for increasing the accuracy of learning algorithms. However, it has the potential to overfit the training set because its objective i...
Effective prediction of defectprone software modules can enable software developers to focus quality assurance activities and allocate effort and resources more efficiently. Supp...
Transfer learning allows leveraging the knowledge of source domains, available a priori, to help training a classifier for a target domain, where the available data is scarce. Th...