Search results for "Intelligence"
showing 10 items of 6959 documents
2D ECG Image Based Biometric Identification Using Stacked Autoencoders
2021
The handcrafted features extraction methods have achieved remarkable results in ECG based biometric identification. However, they are sensitive to many factors: (1) intra and inter-individual variability, (2) heart rate variability, (3) powerline interference, baseline wander and muscle artifacts. To deal with these issues, deep learning approaches have been proposed to extract automatically the important features almost from original data without any preprocessing step (i.e., The original ECG signal mostly contains noise). Unlike conventional ECG based biometric approaches, which based either on fiducial and non-fiducial methods, the proposed approach can be implemented on end to end syste…
Local Directional Multi Radius Binary Pattern
2018
Face recognition becomes an important task performed routinely in our daily lives. This application is encouraged by the wide availability of powerful and low-cost desktop and embedded computing systems, while the need comes from the integration in too much real world systems including biometric authentication, surveillance, human-computer interaction, and multimedia management. This article proposes a new variant of LBP descriptor referred as Local Directional Multi Radius Binary Pattern (LDMRBP) as a robust and effective face descriptor. The proposed LDMRBP operator is built using new neighborhood topology and new pattern encoding scheme. The adopted face recognition system consists of th…
BED: A new dataset for EEG-based biometrics
2021
Various recent research works have focused on the use of electroencephalography (EEG) signals in the field of biometrics. However, advances in this area have somehow been limited by the absence of a common testbed that would make it possible to easily compare the performance of different proposals. In this work, we present a data set that has been specifically designed to allow researchers to attempt new biometric approaches that use EEG signals captured by using relatively inexpensive consumer-grade devices. The proposed data set has been made publicly accessible and can be downloaded from https://doi.org/10.5281/zenodo.4309471 . It contains EEG recordings and responses from 21 individuals…
Exploiting Imperfections in Perception-Action Learning
2019
In this paper a some examples of simulations and experiments performed in the last few years in the field of bio-inspired robotics are reviewed and revisited, deepening their characteristics and emphasising the role of imperfections that could be the main actors guiding their success in real environment. Our cases of study rely on both geetic and behavioral experiments on the fruit fly, from which models, simulations and robotic experiments were performed.
Duration of untreated psychosis in first-episode psychosis is not associated with common genetic variants for major psychiatric conditions: results f…
2021
The EU-GEI Project is funded by the European Community’s Seventh Framework Programme under grant agreement No. HEALTH-F2-2010–241909 (Project EU-GEI).
Experimental study of electrical FitzHugh-Nagumo neurons with modified excitability
2006
International audience; We present an electronical circuit modelling a FitzHugh-Nagumo neuron with a modified excitability. To characterize this basic cell, the bifurcation curves between stability with excitation threshold, bistability and oscillations are investigated. An electrical circuit is then proposed to realize a unidirectional coupling between two cells, mimicking an inter-neuron synaptic coupling. In such a master-slave configuration, we show experimentally how the coupling strength controls the dynamics of the slave neuron, leading to frequency locking, chaotic behavior and synchronization. These phenomena are then studied by phase map analysis. The architecture of a possible ne…
INTEGRAL/RXTE Observations of Cygnus X-1
2003
We present first results from contemporaneous observations of Cygnus X-1 with INTEGRAL and RXTE, made during INTEGRAL's performance verification phase in 2002 November and December. Consistent with earlier results, the 3-250 keV data are well described by Comptonization spectra from a Compton corona with a temperature of kT~50-90 keV and an optical depth of tau~1.0-1.3 plus reflection from a cold or mildly ionized slab with a covering factor of Omega/2pi~0.2-0.3. A soft excess below 10 keV, interpreted as emission from the accretion disk, is seen to decrease during the 1.5 months spanned by our observations. Our results indicate a remarkable consistency among the independently calibrated de…
A Robust Generic Method for Grid Detection in White Light Microscopy Malassez Blade Images in the Context of Cell Counting
2015
AbstractIn biology, cell counting is a primary measurement and it is usually performed manually using hemocytometers such as Malassez blades. This work is tedious and can be automated using image processing. An algorithm based on Fourier transform filtering and the Hough transform was developed for Malassez blade grid extraction. This facilitates cell segmentation and counting within the grid. For the present work, a set of 137 images with high variability was processed. Grids were accurately detected in 98% of these images.
Free segmentation in rendered 3D images through synthetic impulse response in integral imaging
2016
Integral Imaging is a technique that has the capability of providing not only the spatial, but also the angular information of three-dimensional (3D) scenes. Some important applications are the 3D display and digital post-processing as for example, depth-reconstruction from integral images. In this contribution we propose a new reconstruction method that takes into account the integral image and a simplified version of the impulse response function (IRF) of the integral imaging (InI) system to perform a two-dimensional (2D) deconvolution. The IRF of an InI system has a periodic structure that depends directly on the axial position of the object. Considering different periods of the IRFs we …
Sparse Deconvolution Using Support Vector Machines
2008
Sparse deconvolution is a classical subject in digital signal processing, having many practical applications. Support vector machine (SVM) algorithms show a series of characteristics, such as sparse solutions and implicit regularization, which make them attractive for solving sparse deconvolution problems. Here, a sparse deconvolution algorithm based on the SVM framework for signal processing is presented and analyzed, including comparative evaluations of its performance from the points of view of estimation and detection capabilities, and of robustness with respect to non-Gaussian additive noise. Publicado