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This thesis explores the application of ensemble methods to sequential learning tasks. The focus is on the development and the critical examination of new methods or novel applications of existing methods, with emphasis on supervised and reinforcement lear ...
A brain-computer interface (BCI) is a system that enables control of devices or communication with other persons, only through cerebral activity, without using muscles. The main application for BCIs is assistive technology for disabled persons. Examples fo ...
In this work we analyze and combine evidences from different classifiers for phoneme recognition using information from the confusion matrices. Speech signals are processed to extract the Perceptual Linear Prediction (PLP) and Multi-RASTA (MRASTA) features ...
State-of-the-art database design tools rely on the query optimizer for comparing between physical design alternatives. Although it provides an appropriate cost model for physical design, query optimization is a computationally expensive process. The signif ...
Several papers have already shown the interest of using multiple classifiers in order to enhance the performance of biometric person authentication systems. In this paper, we would like to argue that the core task of Biometric Person Authentication is actu ...
Several papers have already shown the interest of using multiple classifiers in order to enhance the performance of biometric person authentication systems. In this paper, we would like to argue that the core task of Biometric Person Authentication is actu ...
This paper introduces a discriminative model for the retrieval of images from text queries. Our approach formalizes the retrieval task as a ranking problem, and introduces a learning procedure optimizing a criterion related to the ranking performance. The ...
The scores returned by support vector machines are often used as a confidence measures in the classification of new examples. However, there is no theoretical argument sustaining this practice. Thus, when classification uncertainty has to be assessed, it i ...
While feature point recognition is a key component of modern approaches to object detection, existing approaches require computationally expensive patch preprocessing to handle perspective distortion. In this paper, we show that formulating the problem in ...
The goal of this work is to provide robust and accurate speech detection for automatic speech recognition (ASR) in meeting room settings. The solution is based on computing long-term modulation spectrum, and examining specific frequency range for dominant ...
