Listar por autor "Silva-Coira, Fernando"

Mostrando ítems 1-10 de 10

    • Augmented Thresholds for MONI 

      Martínez-Guardiola, César; Brown, Nathaniel K.; Silva-Coira, Fernando; Köppl, Dominik; Gagie, Travis; Ladra, Susana (Institute of Electrical and Electronics Engineers Inc., 2023)
      [Abstract]: MONI (Rossi et al., 2022) can store a pangenomic dataset T in small space and later, given a pattern P, quickly find the maximal exact matches (MEMs) of P with respect to T. In this paper we consider its one-pass ...

    • Compact and indexed representation for LiDAR point clouds 

      Ladra, Susana; Rodríguez Luaces, Miguel; Paramá, José R.; Silva-Coira, Fernando (Taylor & Francis, 2022)
      [Abstract]: LiDAR devices are capable of acquiring clouds of 3D points reflecting any object around them, and adding additional attributes to each point such as color, position, time, etc. LiDAR datasets are usually large, ...

    • Compact data structures for large and complex datasets 

      Silva-Coira, Fernando (2017)
      [Abstract] In this thesis, we study the problem of processing large and complex collections of data, presenting new data structures and algorithms that allow us to efficiently store and analyze them. We focus on three ...

    • Efficient Processing of Raster and Vector Data 

      Silva-Coira, Fernando; Paramá, José R.; Ladra, Susana; López, Juan R.; Gutiérrez, Gilberto (Public Library of Science, 2020-01-10)
      [Abstract] In this work, we propose a framework to store and manage spatial data, which includes new efficient algorithms to perform operations accepting as input a raster dataset and a vector dataset. More concretely, we ...

    • Efficient Representation of Multidimensional Data over Hierarchical Domains 

      Brisaboa, Nieves R.; Cerdeira-Pena, Ana; López López, Narciso; Navarro, Gonzalo; Penabad, Miguel R.; Silva-Coira, Fernando (Springer, 2016-09-21)
      [Abstract] We consider the problem of representing multidimensional data where the domain of each dimension is organized hierarchically, and the queries require summary information at a different node in the hierarchy of ...

    • Indexing and Retrieval of Scores by Humming based on Extracted Features 

      Romero-Velo, Hilda; Ladra, Susana; Paramá, José R.; Silva-Coira, Fernando (Universidade da Coruña, Servizo de Publicacións, 2023)
      [Abstract] In order to be able to conduct searches over large collections of music scores with queries provided in audio format, this article considers recent literature in the field and proposes an implementation to ...

    • Map algebra on raster datasets represented by compact data structures 

      Silva-Coira, Fernando; Paramá, José R.; Ladra, Susana (John Wiley and Sons, 2023-06)
      [Abstract]: The increase in the size of data repositories has forced the design of new computing paradigms to be able to process large volumes of data in a reasonable amount of time. One of them is in-memory computing, ...

    • Scalable processing and autocovariance computation of big functional data 

      Brisaboa, Nieves R.; Cao, Ricardo; Paramá, José R.; Silva-Coira, Fernando (John Wiley & Sons, 2018)
      [Abstract]: This paper presents 2 main contributions. The first is a compact representation of huge sets of functional data or trajectories of continuous-time stochastic processes, which allows keeping the data always ...

    • Space-Efficient Representations of Raster Time Series 

      Silva-Coira, Fernando; Paramá, José R.; Bernardo, Guillermo de; Seco, Diego (Elsevier, 2021)
      [Abstract] Raster time series, a.k.a. temporal rasters, are collections of rasters covering the same region at consecutive timestamps. These data have been used in many different applications ranging from weather forecast ...

    • Towards a Compact Representation of Temporal Rasters 

      Cerdeira-Pena, Ana; Bernardo, Guillermo de; Fariña, Antonio; Paramá, José R.; Silva-Coira, Fernando (Springer Nature, 2018-09)
      [Abstract]: Big research efforts have been devoted to efficiently manage spatio-temporal data. However, most works focused on vectorial data, and much less, on raster data. This work presents a new representation for raster ...