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In this paper, a brain/computer interface is proposed. The aim of this work is the recognition of the will of a human being, without the need of detecting the movement of any muscle. Disabled people could take, of course, most important advantages from this kind of sensor system, but it could also be useful in many other situations where arms and legs could not be used or a brain-computer interface...
Laser detection and tracking of aircrafts based systems (LIDARs, LIgth Detection And Ranging systems) are emerging as a critical design trend in development of new generation ATM (Air Traffic Management) paradigms, of which they are the main innovations. The main goal of the presented project is therefore to develop a novel laser tracking technology (SKY-Scanner System) capable to detect and track...
In this paper, a statistical analysis had been carried out on the measured joint angles of the human hand's fingers while performing some common tasks. By exploiting the correlation existing on some couples of joints, we can reduce the number of myoelectric sensors necessary to drive a (virtual or real) hand prosthesis, while still maintaining an acceptable hand's Degree of Freedom (DoF). In order...
Air Traffic Management (ATM) is traditionally performed by means of radar systems, but new detection and ranging systems based on LIDAR (LIgth Detection And Ranging systems) are emerging as a critical design trend and yielding to new generation ATM paradigms. The main goal of the designers of the system under discussion was to develop a novel laser tracking technology (SKY-Scanner System) that could...
In this paper, a brain/computer interface is proposed. The aim of this work is the recognition of the will of a human being, without the need of detecting the movement of any muscle. Disabled people could take, of course, most important advantages from this kind of sensor system, but it could also be useful in many other situations where arms and legs could not be used or a brain-computer interface...
In this paper, a method for symmetry axis detection in binary images is presented. The method is an improvement of a previous method presented by the same authors. The method exploits the nonlinear dynamic behavior of cellular neural networks (CNNs), in particular the propagation of bipolar waves. The image is represented in polar form, transforming the symmetry with respect to an arbitrarily oriented...
In this paper we propose an algorithm that is able to detect moving objects, returning the number of found objects, together with their position, shape, and approximate distance. The system is based on two cameras, which are supposed to be fixed, a digital processor, and two analog chips, which perform data analysis. The use of a couple of cameras improves the performance in comparison with systems...
In this paper we propose a sensor interface that is able to detect moving objects, returning the number of found objects, together with their position, shape, and approximate distance. The system is based on two cameras, which are supposed to be fixed, a digital processor, and two analog chips, which perform data analysis. The use of a couple of cameras improves the performance in comparison with...
A moving objects detection algorithm is proposed in order to improve the performance in presence of moving objects appearing close in a 2D image but with different distances from the observer. The method requires two distinct cameras with slight horizontal displacement, giving two video sequences. Frame difference is used to evidence the moving objects from the background in each video sequence. Then...
In this paper a method for symmetry axis detection in binary images is presented. The method exploits the nonlinear dynamic behavior of cellular neural networks (CNNs), in particular the propagation of bipolar waves. The image is represented in polar form, transforming the symmetry with respect to an arbitrarily oriented axis in a vertical symmetry: the position of the vertical axis corresponds to...
A novel algorithm for unsupervised classification of datasets made up of integer valued patterns by means of cellular neural network (CNN) is proposed. The algorithm is suited both for linearly separable and nonlinearly separable data sets. The adopted CNN is n-dimensional and is based on a space-variant template - neighborhood order 1 - to cluster n-dimensional datasets. The choice of a CNN architecture...
The relation existing between support vector machines (SVMs) and recurrent associative memories is investigated. The design of associative memories based on the generalized brain-state-in-a-box (GBSB) neural model is formulated as a set of independent classification tasks which can be efficiently solved by standard software packages for SVM learning. Some properties of the networks designed in this...
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