Listar por autor "Regueiro, Carlos V."

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    • Concept Drift Detection and Adaptation for Federated and Continual Learning 

      Casado, Fernando E.; Lema, Dylan; Criado, Marcos F.; Iglesias, Roberto; Regueiro, Carlos V.; Barro, Senén (Springer, 2021)
      [Abstract] Smart devices, such as smartphones, wearables, robots, and others, can collect vast amounts of data from their environment. This data is suitable for training machine learning models, which can significantly ...

    • Efficient Parallel Numerical Solver for the Elastohydrodynamic Reynolds–Hertz Problem 

      Arenaz Silva, Manuel; Doallo, Ramón; Touriño, Juan; Regueiro, Carlos V. (Elsevier BV * North-Holland, 2001-12-01)
      [Abstract] This work presents a parallel version of a complex numerical algorithm for solving an elastohydrodynamic piezoviscous lubrication problem studied in tribology. The numerical algorithm combines regula falsi, fixed ...

    • Incremental Learning from Low-labelled Stream Data in Open-Set Video Face Recognition 

      López-López, Eric; Pardo, Xosé Manuel; Regueiro, Carlos V. (Elsevier, 2022)
      [Abstract] Deep Learning approaches have brought solutions, with impressive performance, to general classification problems where wealthy of annotated data are provided for training. In contrast, less progress has been ...

    • Mobile Robot Positioning with 433-MHz Wireless Motes with Varying Transmission Powers and a Particle Filter 

      Canedo-Rodríguez, Adrián; Rodríguez, José Manuel; Álvarez-Santos, Víctor; Iglesias, Roberto; Regueiro, Carlos V. (Multidisciplinary Digital Publishing Institute, 2015)
      In wireless positioning systems, the transmitter’s power is usually fixed. In this paper, we explore the use of varying transmission powers to increase the performance of a wireless localization system. To this extent, we ...

    • Non-IID data and Continual Learning processes in Federated Learning: A long road ahead 

      Criado, Marcos F.; Casado, Fernando E.; Iglesias Rodríguez, Roberto; Regueiro, Carlos V.; Barro, Senén (Elsevier, 2022)
      [Abstract] Federated Learning is a novel framework that allows multiple devices or institutions to train a machine learning model collaboratively while preserving their data private. This decentralized approach is prone ...

    • Self-Organized Multi-Camera Network for a Fast and Easy Deployment of Ubiquitous Robots in Unknown Environments 

      Canedo-Rodríguez, Adrián; Iglesias, Roberto; Regueiro, Carlos V.; Álvarez-Santos, Víctor; Pardo, Xosé Manuel (Multidisciplinary Digital Publishing Institute, 2013)
      To bring cutting edge robotics from research centres to social environments, the robotics community must start providing affordable solutions: the costs must be reduced and the quality and usefulness of the robot services ...

    • Towards a Self-Sufficient Face Verification System 

      López-López, Eric; Regueiro, Carlos V.; Pardo, Xosé Manuel; Franco, Annalisa; Lumini, Alessandra (Elsevier, 2021)
      [Abstract] The absence of a previous collaborative manual enrolment represents a significant handicap towards designing a face verification system for face re-identification purposes. In this scenario, the system must learn ...

    • Walking Recognition in Mobile Devices 

      Casado, Fernando E.; Rodríguez García, Germán; Iglesias Rodríguez, Roberto; Regueiro, Carlos V.; Barro, Senén; Canedo-Rodriguez, Adrián (MDPI AG, 2020-02-21)
      [Abstract] Presently, smartphones are used more and more for purposes that have nothing to do with phone calls or simple data transfers. One example is the recognition of human activity, which is relevant information for ...