Abstract. This paper investigates the methods for learning predictive classifiers based on Bayesian belief networks (BN) – primarily unrestricted Bayesian networks and Bayesian m...
Segmentation of speech signals is a crucial task in many types of speech analysis. We present a novel approach at segmentation on a syllable level, using a Bidirectional Long-Shor...
Christian Landsiedel, Jens Edlund, Florian Eyben, ...
Abstract. Probabilistic Neural Networks (PNNs) constitute a promising methodology for classification and prediction tasks. Their performance depends heavily on several factors, su...
Vasileios L. Georgiou, Sonia Malefaki, Konstantino...
In this paper, we propose a two-pass intra-refresh transcoding scheme for inserting error-resilience features to a compressed video at the media gateway of a three-tier streaming ...
— High-speed backbones are regularly affected by various kinds of network anomalies, ranging from malicious attacks to harmless large data transfers. Different types of anomalies...