The detection of two-component mixture alternatives
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We address the need for robust detection of obstructed human features in complex environments, with a focus on intelligent surgical UIs. In our setup, real-time detection is used to find features without the help of local (spatial or temporal) information. ...
Nowadays, state-of-the-art automatic speaker recognition systems show very good performance in discriminating between voices of speakers under controlled recording conditions. However, the conditions in which recordings are made in investigative activities ...
Model-based statistical analysis of functional magnetic resonance imaging (fMRI) data relies on the general linear model and statistical hypothesis testing. Due to the large number of intracranial voxels, it is important to deal with the multiple compariso ...
This thesis addresses text-independent speaker verification from a machine learning point of view. We use the machine learning framework to better define the problem and to develop new unbiased performance measures and statistical tests to compare objectiv ...
We consider here how to assess if two classifiers, based on a set of test error results, are performing equally well. This question is often considered in the realm of sampling theory, based on classical hypothesis testing. Here we present a simple Bayesia ...
We investigate the distributed successive refinement (SR) hypothesis testing problem. Bivariate hypothesis H-0 : P-XY against H-1 : PXPY, i.e., test against independence is considered, when a remote sensor sends compressed information about data stream X s ...
This paper presents experiments aiming at improving the automatic transcription of oral presentations through the inclusion of the slides in the recognition process. The experiments are performed over a data set of around three hours of material (~33 kword ...
Verifying a person's identity claim by combining multiple biometric systems (fusion) is a promising solution to identity theft and automatic access control. This thesis contributes to the state-of-the-art of multimodal biometric fusion by improving the und ...
Although non-parametric tests have already been proposed for that purpose, statistical significance tests for non-standard measures (different from the classification error) are less often used in the literature. This paper is an attempt at empirically ver ...
Although non-parametric tests have already been proposed for that purpose, statistical significance tests for non-standard measures (different from the classification error) are less often used in the literature. This paper is an attempt at empirically ver ...
