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Classifiers based on Gaussian mixture models are good performers in many pattern recognition tasks. Unlike decision trees, they can be described as stable classifier: a small change in the sampling of the training set will produce not a large change in the ...
Existing approaches to biometric classification with quality measures make a clear distinction between the single-modality applications and the multi-modal scenarios. This study bridges this gap with Q-stack, a stacking-based classifier ensemble, which use ...
Biometric identity verification systems frequently face the challenges of non-controlled conditions of data acquisition. Under such conditions biometric signals may suffer from quality degradation due to extraneous, identity-independent factors. It has bee ...
This paper deals with the influence of age progression on the performance of face verification systems. This is a challenging and largely open research problem that deserves more and more attention. Aging affects both the shape of the face and its texture, ...
A new optimized algorithm for the learning process suitable for hardware implemented Winner Takes Most Kohonen Neural Network (KNN) has been proposed in the paper. In networks of this type a neighborhood mechanism is used to improve the convergence propert ...
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We report on the application of a silicon micromachined lamellar grating interferometer in a Fourier Transform Infrared (FTIR) spectrometer for the detection of gases in the mid-infrared (MIR) region. The FTIR spectrometer was equipped with MIR optical fib ...
Machine-learning based classification techniques have been shown to be effective at detecting objects in complex scenes. However, the final results are often obtained from the alarms produced by the classifiers through a post-processing which typically rel ...
Machine-learning based classification techniques have been shown to be effective at detecting objects in com- plex scenes. However, the final results are often obtained from the alarms produced by the classifiers through a post-processing which typically r ...
We develop an efficient learning framework to construct signal dictionaries for sparse representation by selecting the dictionary columns from multiple candidate bases. By sparse, we mean that only a few dictionary elements, compared to the ambient signal ...
The invention pertains to the field of methods for estimating source signals from a multichannel mixture signal, and the aim of the invention is to carry out a reliable estimation of the properties of source signals without necessarily requiring prior info ...