1,381,497 research outputs found
The Role and Modelling of Presynaptic Inhibition in the Visual Pathway: Applications in Image Processing
No full textPresynaptic Inhibition (PI) basically consists of the strong suppression of a neuron’s response before the stimulus reaches the synaptic terminals mediated by a second, inhibitory, neuron. It has a long lasting effect, greatly potentiated by the action of anaesthetics, that has been observed in motorneurons and in several other places of nervous systems, mainly in sensory processing. In this paper we will focus on several different ways of modelling the effect of PI in the visual pathway as well as the different artificial counterparts derived from such modelling, mainly in two directions: the possibility of computing invariant representations against general changes in illumination of the input image impinging the retina (which is equivalent to a low-level non linear information processing filter) and the role of PI as selector of sets of stimulae that have to be derived to higher brain areas, which, in turn, is equivalent to a “higher-level filter” of information, in the sense of “filtering” the possible semantic content of the information that is allowed to reach later stages of processing.454
A hybrid cloud computing approach for intelligent processing and storage of scientific data
No full textThis paper covers a new approach on Cloud Computing for Scientific Data Storage and Processing using a hybrid system with both on-site and on-the-cloud systems. The system analyzes use cases which are not resolved by either one of the single systems themselves.1881820,329Q
A General Purpouse Control System
No full textIndustrial control applications are developed as ad hoc solutions. These solutions require specific programming and installation, and very often it takes large economic investments. We have developed a system that makes a special effort trying to offer versatility and a solution to a widespread of industrial installations. Our system understands an industrial plant as a compound of sensors, actuators and processes. The user will define its own processes, sensors and actuators. It will also be in his hand the design of the plants visualization diagram. In order to achieve this generalness it is of essence to offer a user interface as friendly as possible. Via a very intuitive user interface the implemented functionalities are far more powerful because the user understand them and makes use of them.11210
Web Applications: A Proposal to Improve Response Time and Its Application to MOODLE
No full textThis paper covers some of the most advanced optimization techniques for web servers and web applications applied to a Modular Object Oriented Distance Learning Environment based on PHP 5 and Apache 2.22521
Newton filters: a new class of neuron-like discrete filters and an application to image processing
No full textThe functions of dentritic trees of neurons have always attracted neuroscientists. Dendrites are extensions of the soma that allows the cell to increase the area where it receives information from. The number of dentritic ramifications is not constant, it depends on the neuron and varies from one to the other. Moreover, each dentritic tree can be subdivided in a. complex form leading to a characteristic tree structure[1]. Two of their immediately-related properties regarding information processing (e.g. convergence and divergence of lines) have originated considerable research on completeness of computation and reliability of transmission [2]. In this paper a layered structure consisting in the interconnections of a set of simple functional units and inspired in the dentritic connections of real neurons, is suggested and in a parallel way we analyze the computing properties and characteristics together with a possible application in Image Processing. The interest of this structure lies in its similarity with the structure of the retinae receptive fields and even with dentritic trees of retinal neurons.342
Application of Multichannel Vision Concepts and Mechanisms in an Artificial Industrial Vision System
No full textThe design of visual processing systems in very demanding industrial environments is a technical field in which bioinspiration has not been explored as a developing tool. The need of extremely quick, accurate and real time responses needed in industrial applications is not usually seen as compatible with the "messy", "slow" or "inaccurate" methods and algorithms inspired in the information processing mechanisms underlying neural activity in the visual pathway. We are trying, thus, to explore the practical possibilities of interaction among concepts from both worlds: the "real" vision system designed for a real time quality control of a production line, and the "inspiration" taken from multichannel biological vision. In previous papers [1,2] a biologically plausible parallel system for visual detection of form, movement, shape and size has been developed. The system, working off-line and skipping real time restrictions, was tested for a variety of situations, yielding very good results in estimating the mentioned visual characteristics of moving objects. Furthermore, a second parallel-computing version was designed introducing the concept of parallel channel processing, e.g., the discrimination of different visual characteristics by mean of multiprocessors and multithread computing. The architecture we present here, which includes certain concepts developed in the previously explained results [3,4], is intended to work in the production line of a beverage canning industry where cans with faulty imprinted use date and lot number have to be immediately discharged from the line.5004920,402Q
On the Evolution of Formal Models and Artificial Neural Architectures for Visual Motion Detection
No full textMotion is a key, basic descriptor of our visual experience of the outside world. The lack of motion perception is a devastating illness that leads to death in animals and seriously impaired behavior in humans. Thus, the study of biological basis of motion detection and analysis and the modelling and artificial implementation of those mechanisms has been a fruitful path of science in the last 60 years. Along this paper, the authors make a review of the main models of motion perception that have emerged since the decade of the 60's stress-ing the underlying biological concepts that have inspired most of them and the traditional architectural concepts imprinted in their functionality and design: formal mathematical analysis, strict geometric patterns of neuron-like processors, selectivity of stimulate etc. Traditional approaches are, then, questioned to include "messy" characteristics of real biological systems such as random distribution of neuron-like processors, non homogeneity of neural architecture, sudden failure of processing units and, in general, non deterministic behavior of the system. As a result is interesting to show that reliability of motion analysis, computational cost and extraction of pure geometrical visual descriptors (size and position of moving objects) besides motion are improved in an implemented model.4884790,402Q
On the Integration of Fractional Neuronal Dynamics Driven by Correlated Processes
No full textThe stochastic Leaky Integrate-and-Fire (LIF) model is revisited adopting a fractional derivative instead of the classical one and a correlated input in place of the usual white noise. The aim is to include in the neuronal model some physiological evidences such as correlated inputs, codified input currents and different time-scales. Fractional integrals of Gauss-Markov processes are considered to investigate the proposed model. Two specific examples are given. Simulations of paths and histograms of first passage times are provided for a specific case
On the estimation of first-passage time densities for a class of Gauss-Markov processes
No full textFor a class of Gauss-Markov processes the asymptotic behavior
of the first passage time (FPT) probability density function (pdf) through certain time-varying boundaries is determined. Computational results for Wiener, Ornstein-Uhlenbeck and Brownian bridge processes are considered to show that the FPT pdf through certain large boundaries exhibits for large times an excellent asymptotic approximatio
Real time vehicle recognition: a novel method for road detection
No full textKnowing the location of the road in an intelligent traffic systems is one of the most used solutions to ease vehicle detection. For this purpose we propose a vehicle recognition algorithm which performs a real time automatic detection of the zones which vehicles occupy. Such algorithm is capable of functioning under extreme conditions such as low resolution, low capture angle and gray scale images.Peer ReviewedPreprin
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