A fast subspace analysis and feature extraction algorithm is proposed which is based on fast Haar transform and integral vector. In rapid object detection and conventional binary ...
The outputs of multi-layer perceptron (MLP) classifiers have been successfully used in tandem systems as features for HMM-based automatic speech recognition. In a previous paper, ...
We consider principal component analysis (PCA) in decomposable Gaussian graphical models. We exploit the prior information in these models in order to distribute its computation. ...
We investigate a method using support vector machines (SVMs) with walk-based graph kernels for high-level feature extraction from images. In this method, each image is first segme...
This paper proposes a data pruning-based compression scheme to improve the rate-distortion relation of compressed images and video sequences. The original frames are pruned to a s...
We introduce a new channel, which consists of an interference channel (IC) in parallel with an interference relay channel (IRC), to analyze the interaction between two selfish and...
Elena Veronica Belmega, Brice Djeumou, Samson Lasa...
This paper proposes and compares four cross-lingual and bilingual automatic speech recognition techniques under the constraints of limited memory size and CPU speed. The first thr...
Several studies have been dedicated to the analysis and modeling of AM–FM modulations in speech and different algorithms have been proposed for the exploitation of modulations i...
In this paper, a new approach for Confocal Microscopy (CM) based on the framework of compressive sensing is developed. In the proposed approach, a point illumination and a random ...
We present two speech transformation approaches designed to increase the intelligibility of speech. The first approach is used in the context of increasing the intelligibility of...