Recent Submissions

  • Panel: Software development methods in the IoT-laden, AI/ML-driven era 

    Marco Gómez, Jordi (Institute of Electrical and Electronics Engineers (IEEE), 2022)
    Conference report
    Restricted access - publisher's policy
    The growing of Internet of Things (IoT) driven with rapid advances in Artificial Intelligence (AI) with special emphasis in Machine Learning (ML) techniques herald a new era of software systems. As we enter this new era ...
  • Relating real and synthetic social networks through centrality measures 

    Blesa Aguilera, Maria Josep; Popa, Mihail Eduard; Serna Iglesias, María José (Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022)
    Conference report
    Open Access
    We perform here a comparative study on the behaviour of real and synthetic social networks with respect to a selection of nine centrality measures. Some of them are topology based (degree, closeness, betweenness), while ...
  • A reinforcement learning path planning approach for range-only underwater target localization with autonomous vehicles 

    Masmitjà Rusiñol, Ivan; Martín Muñoz, Mario; Katija, Kakani; Gomáriz Castro, Spartacus; Navarro Bernabé, Joan (Institute of Electrical and Electronics Engineers (IEEE), 2022)
    Conference report
    Open Access
    Underwater target localization using range-only and single-beacon (ROSB) techniques with autonomous vehicles has been used recently to improve the limitations of more complex methods, such as long baseline and ultra-short ...
  • Testing reinforcement learning explainability methods in a multi-agent cooperative environment 

    Domènech Vila, Marc; Gnatyshak, Dmitry; Tormos Llorente, Adrián; Álvarez Napagao, Sergio (IOS Press, 2022)
    Conference report
    Open Access
    The adoption of algorithms based on Artificial Intelligence (AI) has been rapidly increasing during the last years. However, some aspects of AI techniques are under heavy scrutiny. For instance, in many cases, it is not ...
  • Focus and bias: will it blend? 

    Arias Duart, Anna; Parés Pont, Ferran; Giménez Ábalos, Víctor; Garcia Gasulla, Dario (IOS Press, 2022)
    Conference report
    Open Access
    One direct application of explainable AI feature attribution methods is to be used for detecting unwanted biases. To do so, domain experts typically have to review explained inputs, checking for the presence of unwanted ...
  • Optimizing online time-series data imputation through case-based reasoning 

    Pascual Pañach, Josep; Sànchez-Marrè, Miquel; Cugueró Escofet, Miquel Àngel (IOS Press, 2022)
    Conference report
    Open Access
    When working with Intelligent Decision Support Systems (IDSS), data quality could compromise decisions and therefore, an undesirable behaviour of the supported system. In this paper, a novel methodology for time-series ...
  • Long short-term memory to predict 3D amino acids positions in GPCR molecular dynamics 

    López Correa, Juan Manuel; König, Caroline; Vellido Alcacena, Alfredo (IOS Press, 2022)
    Conference report
    Open Access
    G-Protein Coupled Receptors (GPCRs) are a big family of eukaryotic cell transmembrane proteins, responsible for numerous biological processes. From a practical viewpoint around 34% of the drugs approved by the US Food and ...
  • Deep Air: A smart city AI synthetic data digital twin solving the scalability data problems 

    Almirall, Esteve; Callegaro, Davide; Bruins, Peter; Santamaría Varas, Mar; Martínez Díez, Pablo; Cortés García, Claudio Ulises (IOS Press, 2022)
    Conference report
    Open Access
    Cities are becoming data-driven, re-engineering their processes to adapt to dynamically changing needs. A.I. brings new capabilities, effectively enlarging the space of policy interventions that can be explored and applied. ...
  • Automatic vehicle counting area creation based on vehicle deep learning detection and DBSCAN 

    Alvarez Piña, Gerardo; Moya Sánchez, Eduardo Ulises; Sánchez-Pérez, Abraham; Cortés García, Claudio Ulises (Institute of Electrical and Electronics Engineers (IEEE), 2022)
    Conference report
    Open Access
    Deep learning and high-performance computing have augmented and speed-up the scope of video-based vehicles' massive counting. The automatic vehicle counts result from the detection and tracking of the vehicles in certain ...
  • Obstruction level detection of sewers videos using convolutional neural networks 

    Gutiérrez Mondragón, Mario Alberto; Garcia Gasulla, Dario; Álvarez Napagao, Sergio; Brossa Ordoñez, Jaume; Gimenez Esteban, Rafael (International journal of structural and civil engineering research (IJSCER), 2021)
    Conference report
    Open Access
    Worldwide, sewer networks are designed to transport wastewater to a centralized treatment plant to be treated and returned to the environment. This is a critical process for preventing waterborne illnesses, providing safe ...
  • Results and lessons learned from the Barcelona ZeroG Challenge 

    Pérez Poch, Antoni; Monsalve, María del Pilar; Mejía, Oriana; Mendoza, Luisa F.; Quintero, Paulina; Bustamante, Liliana M.; Ventura Gonzalez Alonso, Daniel (International Astronautical Federation, 2022)
    Conference lecture
    Restricted access - publisher's policy
  • Assessment of the immune cell counting obtained from human peripheral blood after a parabolic flight 

    Gorgori, Abril; Pérez Poch, Antoni; Ventura Gonzalez Alonso, Daniel; Petriz, Jordi; Viscor Carrasco, Ginés (International Astronautical Federation, 2022)
    Conference lecture
    Restricted access - publisher's policy

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