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We discuss approaches to incrementally construct an ensemble. The first constructs an ensemble of classifiers choosing a subset from a larger set, and the second constructs an ensemble of discriminants, where a classifier is used for some classes only. We investigate criteria including accuracy, significant improvement, diversity, correlation, and the role(More)
In this paper, we present an extensive study of 3D face recognition algorithms and examine the benefits of various score-, rank-, and decision-level fusion rules. We investigate face recognizers from two perspectives: the data representation techniques used and the feature extraction algorithms that match best each representation type. We also consider(More)
We propose to approach the detection of patients affected by schizophrenia by means of dissimilarity-based classification techniques applied to brain magnetic resonance images. Instead of working with features directly, pairwise distances between expert delineated regions of interest (ROIs) are considered as representations based on which learning and(More)
The controller or the “control plane” is at the heart of software defined networks (SDN). As SDN migrates to wide area networks (WAN), scalability and performance are two important factors that differentiate one controller from another, and they are critical for success of SDN for end-to-end service management. We distinguish control flows(More)
The evolution of mobile telecommunication networks is accompanied by new demands for the performance, portability, elasticity, and energy efficiency of network functions. Network Function Virtualization (NFV), Software Defined Networking (SDN), and cloud service technologies are claimed to be able to provide most of the capabilities. However, great leap(More)
In this paper, we propose a hybrid generative/discriminative classification scheme and apply it to the detection of renal cell carcinoma (RCC) on tissue microarray (TMA) images. In particular we use probabilistic latent semantic analysis (pLSA) as a generative model to perform generative embedding onto the free energy score space (FESS). Subsequently, we(More)
OBJECTIVES Frequency of pulmonary complications after renal transplant has been reported to range from 3% to 17%. The objective of this study was to evaluate renal transplant recipients admitted to an intensive care unit to identify incidence and cause of acute respiratory failure in the postoperative period and compare clinical features and outcomes(More)
Automatic decisional systems based on pattern classification methods are becoming very important to support medical diagnosis. In general, the overall objective is to classify between healthy subjects and patients affected by a certain disease. To reach this aim, significant efforts have been spent in finding reliable biomarkers which are able to robustly(More)