In this paper, we present experiments comparing different training algorithms for Radial Basis Functions (RBF) neural networks. In particular we compare the classical training which consist of an unsupervised training of centers followed by a supervised training of the weights at the output, with the full supervised training by gradient descent proposed recently in same papers. We conclude that...

Organizations need effective and affordable software training. In face-to-face settings, behavior modeling (BM) is an effective, but expensive, training method. Can BM be employed effectively, and more affordably, for software training in the online environment? An experiment was conducted to compare the effectiveness of online BM with that of face-to-face (F2F) BM for software training. Result...

In this paper, we present experiments comparing different training algorithms for Radial Basis Functions (RBF) neural networks. In particular we compare the classical training which consists of an unsupervised training of centers followed by a supervised training of the weights at the output, with the full supervised training by gradient descent proposed recently in same papers. We conclude tha...

Event-related potential (ERP)-based brain-computer interfacing (BCI) is an effective method of basic communication. However, collecting calibration data, and classifier training, detracts from the amount of time allocated for online communication. Decreasing calibration time can reduce preparation time thereby allowing for additional online use, potentially lower fatigue, and improved performan...

multiple people detection and tracking is a challenging task in real-world crowded scenes. in this paper, we have presented an online multiple people tracking-by-detection approach with a single camera. we have detected objects with deformable part models and a visual background extractor. in the tracking phase we have used a combination of support vector machine (svm) person-specific classifie...

Current training strategies implemented in online WBT training sessions are rather simple strategies. They lack a number of aspects of typical classroom training strategies, such as composite training strategies, possibility to customize and adapt training strategy, collaborative training strategies, and so on. In this paper we present a novel WBT tool called Virtual Classrooms, which we implem...

Growing neural gas (GNG) has been successfully applied to unsupervised learning problems. However, GNG-inspired approaches can also be applied to classification problems, provided they are extended with an appropriate labelling function. Most approaches along these lines have so far relied on strategies which label neurons a posteriori, after the training has been completed. As a consequence, s...