Automatic speech recognition can fail to a certain extent when confronted with emotionally distorted speech. Great efforts have been spent so far to cope with noise conditions or speaker’s characteristics. Yet, adaptation to the emotional condition of the speaker could help to further improve the overall performance. In this respect we aim at a robust and reliable recognition of the speaker’s e...

An ensemble of classifiers is a set of classification models and a method to combine their predictions into a joint decision. They were primarily devised to improve classification accuracies over individual classifiers. However, the growing need for learning from very large data sets has opened new application areas for this strategy. According to this approach, new ensembles of classifiers hav...

In this paper, a rapid adaptive pedestrian detection method based on cascade classifier with ternary pattern is proposed. The proposed method achieves its goal by employing the following three new strategies: (1) A method for adjusting the key parameters of the trained cascade classifier dynamically for detecting pedestrians in unseen scenes using only a small amount of labeled data from the ne...

In this paper, an experimental comparison between fixed and trained fusion rules for multimodal personal identity verification is reported. We focused on the behaviour of the considered fusion methods for ensembles of classifiers exhibiting significantly different performance, as this is one of the main characteristics of multimodal biometrics systems. The experiments were carried out on the XM...

In this paper we present two improvements over Viola and Jones [1] training scheme for face detection. The first is 300-fold speed improvement over the training method presented by Viola and Jones [1] with a modest increase in execution time. The second is a principled method for determining a cascade classifier of optimal speed. We present some preliminary results of our methods.