Uma proposição para o cálculo de mapas de disparidade de imagens estéreo usando um interpolador neural baseado em funções de base radial

This study aims to seek a more viable alternative for the calculation of differences in images of stereo vision, using a factor that reduces heel the amount of points that are considered on the captured image, and a network neural-based radial basis functions to interpolate the results. The objective to be achieved is to produce an approximate picture of disparities using algorithms with low computational cost, unlike the classical algorithms

Contribuições a técnicas de agrupamento e visualização de dados multivariados utilizando mapas auto-organizáveis

Self-organizing maps (SOM) are artificial neural networks widely used in the data mining field, mainly because they constitute a dimensionality reduction technique given the fixed grid of neurons associated with the network. In order to properly the partition and visualize the SOM network, the various methods available in the literature must be applied in a post-processing stage, that consists of inferring, through its neurons, relevant characteristics of the data set. In general, such processing applied to the network neurons, instead of the entire database, reduces the computational costs due to vector quantization. This work proposes a post-processing of the SOM neurons in the input and output spaces, combining visualization techniques with algorithms based on gravitational forces and the search for the shortest path with the greatest reward. Such methods take into account the connection strength between neighbouring neurons and characteristics of pattern density and distances among neurons, both associated with the position that the neurons occupy in the data space after training the network. Thus, the goal consists of defining more clearly the arrangement of the clusters present in the data. Experiments were carried out so as to evaluate the proposed methods using various artificially generated data sets, as well as real world data sets. The results obtained were compared with those from a number of well-known methods existent in the literature

Desenvolvimento de um sistema computacional para geração automática de mapas de vulnerabilidade como ferramenta de auxílio às ações de prevenção ao derramamento de óleo em áreas costeiras

The northern portion of the Rio Grande do Norte State is characterized by intense coastal dynamics affecting areas with ecosystems of moderate to high environmental sensitivity. In this region are installed the main socioeconomic activities of RN State: salt industry, shrimp farm, fruit industry and oil industry. The oil industry suffers the effects of coastal dynamic action promoting problems such as erosion and exposure of wells and pipelines along the shore. Thus came the improvement of such modifications, in search of understanding of the changes which causes environmental impacts with the purpose of detecting and assessing areas with greater vulnerability to variations. Coastal areas under influence oil industry are highly vulnerable and sensitive in case of accidents involving oil spill in the vicinity. Therefore, it was established the geoenvironmental monitoring of the region with the aim of evaluating the entire coastal area evolution and check the sensitivity of the site on the presence of oil. The goal of this work was the implementation of a computer system that combines the needs of insertion and visualization of thematic maps for the generation of Environmental Vulnerability maps, using techniques of Business Intelligence (BI), from vector information previously stored in the database. The fundamental design interest was to implement a more scalable system that meets the diverse fields of study and make the appropriate system for generating online vulnerability maps, automating the methodology so as to facilitate data manipulation and fast results in cases of real time operational decision-making. In database development a geographic area was established the conceptual model of the selected data and Web system was done using the template database PostgreSQL, PostGis spatial extension, Glassfish Web server and the viewer maps Web environment, the GeoServer. To develop a geographic database it was necessary to generate the conceptual model of the selected data and the Web system development was done using the PostgreSQL database system, its spatial extension PostGIS, the web server Glassfish and GeoServer to display maps in Web