Nature Inspired Problem-Solving Methods in Knowledge Engineering
Second International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2007, La Manga del Mar Menor, Spain, June 18-21, 2007, Proceedings, Part II

José Mira, José R. Álvarez

Items from 1 to 20 out of 67 results

chapter

Back Matter

Lecture Notes in Computer Science > Nature Inspired Problem-Solving Methods in Knowledge Engineering

chapter

High Performance Implementation of an FPGA-Based Sequential DT-CNN

J. Javier Martínez-Alvarez, F. Javier Garrigós-Guerrero, F. Javier Toledo-Moreo, J. Manuel Ferrández-Vicente

Lecture Notes in Computer Science > Nature Inspired Problem-Solving Methods in Knowledge Engineering > 1-9

In this paper an FPGA-based implementation of a sequential discrete time cellular neural network (DT-CNN) with 3×3 templates is described. The architecture is based on a single pipelined cell which is employed to emulate a CNN with larger number of neurons. This solution diminishes the use of hardware resources on the FPGA and allows the cell to process real time input data in a sequential mode. Highly...

chapter

HANNA: A Tool for Hardware Prototyping and Benchmarking of ANNs

Javier Garrigós, José J. Martínez, Javier Toledo, José M. Ferrández

Lecture Notes in Computer Science > Nature Inspired Problem-Solving Methods in Knowledge Engineering > 10-18

The continuous advances in VLSI technologies, computer architecture and software development tools make it difficult to find the adequate implementation platform of an ANN for a given application. This paper describes HANNA, a software tool designed to automate the generation of hardware prototypes of MLP and MLP-like neural networks over FPGA devices. Coupled with traditional Matlab^®/Simulink^® environments...

chapter

Improvement of ANNs Performance to Generate Fitting Surfaces for Analog CMOS Circuits

José Ángel Díaz-Madrid, Pedro Monsalve-Campillo, Juan Hinojosa, María Victoria Rodellar Biarge, more

Lecture Notes in Computer Science > Nature Inspired Problem-Solving Methods in Knowledge Engineering > 19-27

One of the typical applications of neural networks is based on their ability to generate fitting surfaces. However, for certain problems, error specifications are very restrictive, and so, the performance of these networks must be improved. This is the case of analog CMOS circuits, where models created must provide an accuracy which some times is difficult to achieve using classical techniques. In...

chapter

Wavelet Network for Nonlinearities Reduction in Multicarrier Systems

Nibaldo Rodriguez, Claudio Cubillos, Orlando Duran

Lecture Notes in Computer Science > Nature Inspired Problem-Solving Methods in Knowledge Engineering > 28-36

In this paper, we propose a wavelet neural network suitable for reducing nonlinear distortion introduced by a traveling wave tube amplifier (TWTA) over multicarrier systems. Parameters of the proposed network are identified using an hybrid training algorithm, which adapts the linear output parameters using the least square algorithm and the nonlinear parameters of the hidden nodes are trained using...

chapter

Improved Likelihood Ratio Test Detector Using a Jointly Gaussian Probability Distribution Function

O. Pernía, J. M. Górriz, J. Ramírez, C. G. Puntonet, more

Lecture Notes in Computer Science > Nature Inspired Problem-Solving Methods in Knowledge Engineering > 37-44

Currently, the accuracy of speech processing systems is stro- ngly affected by the acoustic noise. This is a serious obstacle to meet the demands of modern applications and therefore these systems often needs a noise reduction algorithm working in combination with a precise voice activity detector (VAD). This paper presents a new voice activity detector (VAD) for improving speech detection robustness...

chapter

Performance Monitoring of Closed-Loop Controlled Systems Using dFasArt

Jose Manuel Cano-Izquierdo, Julio Ibarrola, Miguel Almonacid

Lecture Notes in Computer Science > Nature Inspired Problem-Solving Methods in Knowledge Engineering > 45-53

This paper analyzes the behaviour of closed-loop controlled systems. Starting from the measured data, the aim is to establish a classification of the system operation states. Digital Signal Processing is used to represent temporal signal with spatial patterns. A neuro-fuzzy scheme (dFasArt) is proposed to classify these patterns, in an on-line way, characterizing the state of controller performance...

chapter

Normalising Brain PET Images

Elia Ferrando Juliá, Daniel Ruiz Fernández, Antonio Soriano Payá

Lecture Notes in Computer Science > Nature Inspired Problem-Solving Methods in Knowledge Engineering > 54-62

PET is a nuclear medical examination which constructs a three-dimensional image of metabolism inside the body; in this article in particular, images are taken from the brain. The high complexity inherent to the interpretation of the brain images makes that any help is important to the specialists in order to accurate the diagnostic. In order to reach reliable and good images, a normalization process...

chapter

Automatic Segmentation of Single and Multiple Neoplastic Hepatic Lesions in CT Images

Marcin Ciecholewski, Marek R. Ogiela

Lecture Notes in Computer Science > Nature Inspired Problem-Solving Methods in Knowledge Engineering > 63-71

This paper describes an automatic method for segmenting single and multiple neoplastic hepatic lesions in computed-tomography (CT) images. The structure of the liver is first segmented using the approximate contour model. Then, the appropriate histogram transformations are performed to enhance neoplastic focal lesions in CT images. To segment neoplastic lesions, images are processed using binary morphological...

chapter

Biometric and Color Features Fusion for Face Detection and Tracking in Natural Video Sequences

Juan Zapata, Ramón Ruiz

Lecture Notes in Computer Science > Nature Inspired Problem-Solving Methods in Knowledge Engineering > 72-80

A system that performs the detection and tracking of a face in real-time in real video sequences is presented in this paper. The face is detected in a complex environment by a model of human colour skin. Very good results are obtained, since the colour segmentation removes almost all the complex background and it is realized to a very high-speed, making the system very robust. On the other hand, fast...

chapter

Identifying Major Components of Pictures by Audio Encoding of Colours

Guido Bologna, Benoît Deville, Thierry Pun, Michel Vinckenbosch

Lecture Notes in Computer Science > Nature Inspired Problem-Solving Methods in Knowledge Engineering > 81-89

The goal of the See ColOr project is to achieve a non-invasive mobility aid for blind users that will use the auditory pathway to represent in real-time frontal image scenes. More particularly, we have developed a prototype which transforms HSL coloured pixels into spatialized classical instrument sounds lasting for 300 ms. Hue is sonified by the timbre of a musical instrument, saturation is one of...

chapter

Towards a Semi-automatic Situation Diagnosis System in Surveillance Tasks

José Mira, Rafael Martínez, Mariano Rincón, Margarita Bachiller, more

Lecture Notes in Computer Science > Nature Inspired Problem-Solving Methods in Knowledge Engineering > 90-98

This paper describes an ongoing project that develops a set of generic components to help humans (semi-automatic system) in surveillance and security tasks in several scenarios. These components are based in the computational model of a set of selective and Active VISual Attention mechanisms with learning capacity (AVISA) and in the superposition of an “intelligence” layer that incorporates the knowledge...

chapter

An Implementation of a General Purpose Attentional Mechanism for Artificial Organisms

J. L. Crespo, A. Faiña, R. J. Duro

Lecture Notes in Computer Science > Nature Inspired Problem-Solving Methods in Knowledge Engineering > 99-108

Attention is a mechanism present in most of the more complex and developed living beings. It is responsible for much of their ability to operate in real time in unstructured and dynamic environments with a limited amount of processing resources. In this paper, an architecture for developing attentional functions in agents is presented. This architecture is based on the concept of attentor and it allows...

chapter

Optimal Cue Combination for Saliency Computation: A Comparison with Human Vision

Alexandre Bur, Heinz Hügli

Lecture Notes in Computer Science > Nature Inspired Problem-Solving Methods in Knowledge Engineering > 109-118

The computer model of visual attention derives an interest or saliency map from an input image in a process that encompasses several data combination steps. While several combination strategies are possible, not all perform equally well. This paper compares main cue combination strategies by measuring the performance of the considered models with respect to human eye movements. Six main combination...

chapter

The Underlying Formal Model of Algorithmic Lateral Inhibition in Motion Detection

José Mira, Ana E. Delgado, Antonio Fernández-Caballero, María T. López, more

Lecture Notes in Computer Science > Nature Inspired Problem-Solving Methods in Knowledge Engineering > 119-129

Many researchers have explored the relationship between recurrent neural networks and finite state machines. Finite state machines constitute the best characterized computational model, whereas artificial neural networks have become a very successful tool for modeling and problem solving. Recently, the neurally-inspired algorithmic lateral inhibition (ALI) method and its application to the motion...

chapter

Novel Strategies for the Optimal Registration of Biomedical Images

Jorge Larrey-Ruiz, Juan Morales-Sánchez, Rafael Verdú-Monedero

Lecture Notes in Computer Science > Nature Inspired Problem-Solving Methods in Knowledge Engineering > 130-141

This paper is intended to address three of the most common problems arising in the field of non-rigid biomedical image registration. Firstly, a regularization term based on fractional-order derivatives is proposed. It can be seen as a generalization of the bio-inspired diffusion and curvature smoothing terms but, since it incorporates features of both regularizers, with this approach it is possible...

chapter

Characterization of Artificial Muscles Using Image Processing

Rafael Berenguer Vidal, Rafael Verdú Monedero, Juan Morales Sánchez, Jorge Larrey Ruiz

Lecture Notes in Computer Science > Nature Inspired Problem-Solving Methods in Knowledge Engineering > 142-151

Artificial muscles are bio-inspired devices formed by several layers of conducting polymers. These devices have the ability of transform electrical energy into mechanical energy through an electrochemical reaction, which is produced by an oxidation or reduction of the polymer due to an electric current. Since the device have a strip shape, this reaction results in a macroscopic swelling and shrinking...

chapter

Segmentation of Sequences of Stereoscopic Images for Modelling Artificial Muscles

Santiago González-Benítez, Rafael Verdú-Monedero, Rafael Berenguer-Vidal, Pedro García-Laencina

Lecture Notes in Computer Science > Nature Inspired Problem-Solving Methods in Knowledge Engineering > 152-161

In this paper, an implementation of the Region Competition algorithm for segmenting stereoscopic video sequences is shown. This algorithm is an essential task in the method in order to obtain a 3D characterization of artificial muscles. Image sequences are acquired by a two-cam computer vision system. Optimal and efficient segmentation of these images is our goal; information obtained from the segmented...

chapter

A Support Vector Method for Estimating Joint Density of Medical Images

Jesús Serrano, Pedro J. García-Laencina, Jorge Larrey-Ruiz, José-Luis Sancho-Gómez

Lecture Notes in Computer Science > Nature Inspired Problem-Solving Methods in Knowledge Engineering > 162-170

Human learning inspires a large amount of algorithms and techniques to solve problems in image understanding. Supervised learning algorithms based on support vector machines are currently one of the most effective methods in machine learning. A support vector approach is used in this paper to solve a typical problem in image registration, this is, the joint probability density function estimation...

chapter

Segmentation of Moving Objects with Information Feedback Between Description Levels

M. Rincón, E. J. Carmona, M. Bachiller, E. Folgado

Lecture Notes in Computer Science > Nature Inspired Problem-Solving Methods in Knowledge Engineering > 171-181

In real sequences, one of the factors that most negatively affects the segmentation process result is the existence of scene noise. This impairs object segmentation which has to be corrected if we wish to have some minimum guarantees of success in the following tracking or classification stages. In this work we propose a generic knowledge-based model to improve the segmentation process. Specifically,...

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Keywords

CLASSIFICATION (2)
COLLISION AVOIDANCE (2)
DFASART (2)
MANEUVER DETECTION (2)
NEURAL NETWORKS (2)
NEURO-FUZZY (2)
3D IMAGES (1)
ACTION SELECTION (1)
AIR POLLUTANT LEVEL (1)
ANN (1)
ANT COLONY OPTIMIZATION (1)
ATTENTION (1)
AUTONOMOUS ROBOTS (1)
BIO-INSPIRED SOLUTIONS TO ENGINEERING (1)
BIOMEDICAL SIGNALS (1)
BRAIN (1)
CLOSED-LOOP SYSTEMS (1)
CONSTRAINT PROGRAMMING (1)
DATA MINING (1)
DIAL-A-RIDE PROBLEM (1)
FIS (1)
FOREST FIRE UNDERSTANDING (1)
FREE-SPACE MEASUREMENTS (1)
FUZZY RULES (1)
GA (1)
GENETIC ALGORITHMS (1)
GENETIC PROGRAMING (1)
HYBRID ALGORITHM (1)
INTELLIGENT VEHICLES (1)
INTRINSIC PLASTICITY (1)
LINEARIZING (1)
MOVEMENT DIRECTION IDENTIFICATION (1)
MULTICARRIER (1)
NCTI (1)
NEAREST NEIGHBOR (1)
NEURO-FUZZY SYSTEMS (1)
NORMALIZE (1)
PARTICLE SWARM (1)
PATTERN RECOGNITION (1)
PERMEABILITY (1)
PERMITTIVITY (1)
PET (1)
PREDICTION (1)
PSO (1)
REACTIVE ROBOTICS (1)
SCHOOLING PERFORMANCE (1)
SENSORIAL PROCESSING (1)
SET PARTITIONING (1)
SOM NEURAL NETWORKS (1)
SWARM INTELLIGENCE (1)
SYNAPTIC METAPLASTICITY (1)
TEMPORAL ANALYSIS (1)
UN-SUPERVISED NEURAL NETWORK (1)
VEGETATION WATER CONTENT (1)
WAVELET NETWORK (1)
WAVELETS (1)
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INFONA - science communication portal

Nature Inspired Problem-Solving Methods in Knowledge Engineering
Second International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2007, La Manga del Mar Menor, Spain, June 18-21, 2007, Proceedings, Part II

Back Matter

High Performance Implementation of an FPGA-Based Sequential DT-CNN

HANNA: A Tool for Hardware Prototyping and Benchmarking of ANNs

Improvement of ANNs Performance to Generate Fitting Surfaces for Analog CMOS Circuits

Wavelet Network for Nonlinearities Reduction in Multicarrier Systems

Improved Likelihood Ratio Test Detector Using a Jointly Gaussian Probability Distribution Function

Performance Monitoring of Closed-Loop Controlled Systems Using dFasArt

Normalising Brain PET Images

Automatic Segmentation of Single and Multiple Neoplastic Hepatic Lesions in CT Images

Biometric and Color Features Fusion for Face Detection and Tracking in Natural Video Sequences

Identifying Major Components of Pictures by Audio Encoding of Colours

Towards a Semi-automatic Situation Diagnosis System in Surveillance Tasks

An Implementation of a General Purpose Attentional Mechanism for Artificial Organisms

Optimal Cue Combination for Saliency Computation: A Comparison with Human Vision

The Underlying Formal Model of Algorithmic Lateral Inhibition in Motion Detection

Novel Strategies for the Optimal Registration of Biomedical Images

Characterization of Artificial Muscles Using Image Processing

Segmentation of Sequences of Stereoscopic Images for Modelling Artificial Muscles

A Support Vector Method for Estimating Joint Density of Medical Images

Segmentation of Moving Objects with Information Feedback Between Description Levels

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Nature Inspired Problem-Solving Methods in Knowledge Engineering
Second International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2007, La Manga del Mar Menor, Spain, June 18-21, 2007, Proceedings, Part II