This paper presents a new statistical approach for learning automatic color image correction. The goal is to parameterize color independently of illumination and to correct color for changes of illumination. This is useful in many image processing applications, such as color image segmentation or background subtraction. The motivation for using a learning approach is to deal with changes of lig...

This paper presents an original hybrid MLP-SVM method for unconstrained handwritten digits recognition. Specialized Support Vector Machines (SVMs) are introduced to improve significantly the MLP performances in local areas around the separation surfaces between each pair of digit classes, in the input pattern space. This hybrid architecture is based on the idea that the correct digit class almo...

This paper concerns dynamic neural networks for signal processing: architectural issues are considered but the paper focuses on learning algorithms that work on-line. Locally recurrent neural networks, namely MLP with IIR synapses and generalization of Local Feedback MultiLayered Networks (LF MLN), are compared to more traditional neural networks, i.e. static MLP with input and/or output buffer...

A signal su ers from nonlinear, linear, and additive distortion when transmitted through a channel. Linear equalizers are commonly used in receivers to compensate for linear channel distortion. As an alternative, nonlinear equalizers have the potential to compensate for all three sources of channel distortion. Previous authors have shown that nonlinear feedforward equalizers based on either mul...

BACKGROUND Muscle LIM protein (MLP) is an essential nuclear regulator of myogenic differentiation. Additionally, it may act as an integrator of protein assembly of the actin-based cytoskeleton. MLP-knockout mice develop a marked cardiac hypertrophy reaction and dilated cardiomyopathy (DCM). MLP is therefore a candidate gene for heritable forms of hypertrophic cardiomyopathy (HCM) and DCM in hum...

In this paper, we present our recent progress on multi-layer perceptron (MLP) based data-driven feature extraction using improved MLP structures. Four-layer MLPs are used in this study. Different signal processing methods are applied before the input layer of the MLP. We show that the first hidden layer of a four-layer MLP is able to detect some basic patterns from the time-frequency plane. KLT...

In this contribution, human face as biometric [1] is considered. Original method of feature extraction from image data is introduced using MLP (multilayer perceptron) and PCA (principal component analysis). This method is used in human face recognition system and results are compared to face recognition system using PCA directly, to a system with direct classification of input images by MLP and...

Gaussian Mixture Model (GMM) and Multi Layer Perceptron (MLP) based acoustic models are compared on a French large vocabulary continuous speech recognition (LVCSR) task. In addition to optimizing the output layer size of the MLP, the effect of the deep neural network structure is also investigated. Moreover, using different linear transformations (time derivatives, LDA, CMLLR) on conventional M...

Monotremes (platypus and echidna) are the descendants of the oldest ancestor of all extant mammals distinguished from other mammals by mode of reproduction. Monotremes lay eggs following a short gestation period and after an even briefer incubation period, altricial hatchlings are nourished over a long lactation period with milk secreted by nipple-less mammary patches located on the female's ab...

PICOT (protein kinase C-interacting cousin of thioredoxin) was previously shown to inhibit pressure overload-induced cardiac hypertrophy, concomitant with an increase in ventricular function and cardiomyocyte contractility. The combined analyses of glutathione S-transferase pull-down experiments and mass spectrometry enabled us to determine that PICOT directly interacts with muscle LIM protein ...