11 resultados para Computação assistiva
em SAPIENTIA - Universidade do Algarve - Portugal
Resumo:
Painterly rendering (non-photorealistic rendering or NPR) aims at translating photographs into paintings with discrete brush strokes, simulating certain techniques (im- or expressionism) and media (oil or watercolour). Recently, our research into visual perception and models of processes in the visual cortex resulted in a new rendering scheme, in which detected lines and edges at different scales are translated into brush strokes of different sizes. In order to prepare a version which is suitable for many users, including children, the design of the interface in terms of window and menu system is very important. Discussions with artists and non-artists led to three design criteria: (1) the interface must reflect the procedures and possibilities that real painters follow and use, (2) it must be based on only one window, and (3) the menu system must be very simple, avoiding a jungle of menus and sub-menus. This paper explains the interface that has been developed.
Resumo:
Tese dout., Engenharia electrónica e computação - Processamento de sinal, Universidade do Algarve, 2008
Resumo:
Tese dout., Engenharia Electrónica e Computação, Universidade do Algarve, 2009
Resumo:
Tese dout., Engenharia Electrónica e Computação, Universidade do Algarve, 2005
Resumo:
Tese dout., Engenharia Electrónica e Computação, Universidade do Algarve, 2009
Resumo:
Prémio de Melhor Artigo de Jovem Investigador atribuído pela empresa Timberlake, apresentado na 1ª Conferência Nacional sobre Computação Simbólica no Ensino e na Investigação - CSEI2012, que decorreu no IST nos dias 2 e 3 de Abril.
Resumo:
Tese de dout., Engenharia Electrónica e Computação, Faculdade de Ciências e Tecnologia, Univ. do Algarve, 2005
Resumo:
Tese de dout., Engenharia Electrónica e Computação, Faculdade de Ciências e Tecnologia, Univ. do Algarve, 2003
Resumo:
All systems found in nature exhibit, with different degrees, a nonlinear behavior. To emulate this behavior, classical systems identification techniques use, typically, linear models, for mathematical simplicity. Models inspired by biological principles (artificial neural networks) and linguistically motivated (fuzzy systems), due to their universal approximation property, are becoming alternatives to classical mathematical models. In systems identification, the design of this type of models is an iterative process, requiring, among other steps, the need to identify the model structure, as well as the estimation of the model parameters. This thesis addresses the applicability of gradient-basis algorithms for the parameter estimation phase, and the use of evolutionary algorithms for model structure selection, for the design of neuro-fuzzy systems, i.e., models that offer the transparency property found in fuzzy systems, but use, for their design, algorithms introduced in the context of neural networks. A new methodology, based on the minimization of the integral of the error, and exploiting the parameter separability property typically found in neuro-fuzzy systems, is proposed for parameter estimation. A recent evolutionary technique (bacterial algorithms), based on the natural phenomenon of microbial evolution, is combined with genetic programming, and the resulting algorithm, bacterial programming, advocated for structure determination. Different versions of this evolutionary technique are combined with gradient-based algorithms, solving problems found in fuzzy and neuro-fuzzy design, namely incorporation of a-priori knowledge, gradient algorithms initialization and model complexity reduction.
Resumo:
Dissertação de mestrado, Engenharia de Sistemas e Computação, Unidade de Ciências Exactas e Humanas, Universidade do Algarve, 1997
Resumo:
Dissertação de mestrado, Engenharia de Sistemas e Computação, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2001