This article investigates the effectiveness of multiclassifier fusion technique on domain adaptation for remote sensing image classification. Since it is impossible to find a method that optimal different datasets, and also difficult select best base classifier domain-invariant features, multiple (MDAF) (MBCF) are proposed achieve more stable superior classification performance. The most crucia...

We developed acoustic and lexical classifiers, based on a boosting algorithm, to assess the separability on arousal and valence dimensions in spontaneous emotional speech. The spontaneous emotional speech data was acquired by inviting subjects to play a first-person shooter video game. Our acoustic classifiers performed significantly better than the lexical classifiers on the arousal dimension....

Researchers continue to focus on the design of pattern recognition systems to achieve the best classification rates. Usually, different classification schemes are developed for the problem at hand, and then by experimental assessment, the best classifier is chosen as the final solution to the problem. However, it has been observed that although one design may outperform the others, the patterns...

Fusion techniques have been widely used in multi-modal biometric authentication systems. While these techniques are mainly applied to combine the outputs of modality-dependent classifiers, they can also be applied to fuse the decisions or scores from a single modality. The idea is to consider the multiple samples extracted from a single modality as independent but coming from the same source. I...

This article describes a new Speaker Discrimination System (SDS), which is a part of an overall project called Audio Documents Indexing based on a Speaker Discrimination System (ADISDS). Speaker discrimination consists in checking whether two speech segments come from the same speaker or not. This research domain presents an important field in biometry, since the voice remains an important feat...

Transformers are critical assets for the reliable operation of power grid. may fail in service if monitoring models do not identify degraded conditions time. Dissolved gas analysis (DGA) focuses on examination dissolved gasses transformer oil to diagnose state a transformer. Fusion black-box (BB) classifiers, also known as an ensemble diagnostics models, have been used improve accuracy across m...

Semantic concept classification is a critical task for content-based video retrieval. Traditional methods of machine learning focus on increasing the accuracy of classifiers or models, and face the problems of inducing new data errors and algorithm complexity. Recent researches show that fusion strategies of ensemble learning have appeared promising for improving the classification performance,...