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The performance of face authentication systems has steadily improved over the last few years. State-of-the-art methods use the projection of the gray-scale face image into a Linear Discriminant subspace as input of a classifier such as Support Vector Machi ...
In this paper, we present a system for image replica detection. The technique is based on the extraction of 162 features corresponding to texture, colour and grey-level characteristics. These features are then weighted and statistically normalized. To impr ...
Machine Learning is a modern and actively developing field of computer science, devoted to extracting and estimating dependencies from empirical data. It combines such fields as statistics, optimization theory and artificial intelligence. In practical task ...
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 ...
The inclusion of mental tasks transitions detection (MTTD) has proven a useful tool in guiding the transduction process of a BCI working under an asynchronous protocol. MTTD allows for the extraction of the signal's contextual information in order to infer ...
Multi-stream based automatic speech recognition (ASR) systems outperform their single stream counterparts, specially in case of noisy speech. The main issues in multi-stream systems are: a) Find the feature streams carrying complementary information, and b ...
Biometric authentication is a process of verifying an identity claim using a person's behavioral and physiological characteristics. Due to vulnerability of the system to environmental noise and variation caused by the user, fusion of several biometric-enab ...
In this paper, we present a system for image replica detection. More specifically, the technique is based on the extraction of 162 features corresponding to texture, color and gray-level characteristics. These features are then weighted and statistically n ...
Classifier performance is often enhanced through combining multiple streams of information. In the context of multi-stream HMM/ANN systems in ASR, a confidence measure widely used in classifier combination is the entropy of the posteriors distribution outp ...
The research deals with the novel application of Support Vector Machines (Support Vector Classification and Support Vector Regression) for the analysis and modelling of spatial environmental data. Multiclass classification of soil types and pollution mappi ...
