Percorrer por autor "de Andrade, Diogo"

A mostrar 1 - 2 de 2
  • Item
    Generating 3D Terrain with 2D Cellular Automata
    (2024-06-01) Fachada, Nuno; Rodrigues, António R.; de Andrade, Diogo; Lopes, Phil; COPELABS - Cognitive and People-centric Computing; HEI-LAB - Human Environment Interaction Lab
    This paper presents an initial exploration on the use of 2D cellular automata (CA) for generating 3D terrains through a simple yet effective additive approach. By experimenting with multiple CA transition rules, this preliminary investigation yielded aesthetically interesting landscapes, hinting at the technique's potential applicability for real-time terrain generation in games.
  • Item
    Generating multidimensional clusters with support lines
    (Elsevier B.V., 2023) Fachada, Nuno; de Andrade, Diogo; COPELABS - Cognitive and People-centric Computing
    Synthetic data is essential for assessing clustering techniques, complementing and extending real data, and allowing for more complete coverage of a given problem’s space. In turn, synthetic data generators have the potential of creating vast amounts of data – a crucial activity when real-world data is at premium – while providing a well-understood generation procedure and an interpretable instrument for methodically investigating cluster analysis algorithms. Here, we present Clugen, a modular procedure for synthetic data generation, capable of creating multidimensional clusters supported by line segments using arbitrary distributions. Clugen is open source, comprehensively unit tested and documented, and is available for the Python, R, Julia, and MATLAB/Octave ecosystems. We demonstrate that our proposal can produce rich and varied results in various dimensions, is fit for use in the assessment of clustering algorithms, and has the potential to be a widely used framework in diverse clustering-related research tasks. Keywords: Synthetic data, Clustering, Data generation, Multidimensional data