Recent Submissions

  • 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 ...
  • 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 ...
  • 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 ...
  • Focus! Rating XAI methods and finding biases 

    Arias Duart, Anna; Parés Pont, Ferran; Garcia Gasulla, Dario; Giménez Ábalos, Víctor (Institute of Electrical and Electronics Engineers (IEEE), 2022)
    Conference report
    Open Access
    AI explainability improves the transparency and trustworthiness of models. However, in the domain of images, where deep learning has succeeded the most, explainability is still poorly assessed. In the field of image ...
  • Towards expert-inspired automatic criterion to cut a dendrogram for real-industrial applications 

    Suman, Shikha; Karna, Ashutosh; Gibert, Karina (IOS Press, 2021)
    Conference report
    Open Access
    Hierarchical clustering is one of the most preferred choices to understand the underlying structure of a dataset and defining typologies, with multiple applications in real life. Among the existing clustering algorithms, ...
  • An adaptable approach to learn realistic legged locomotion without examples 

    Ordonez-Apraez, Daniel; Agudo Martínez, Antonio; Moreno-Noguer, Francesc; Martín Muñoz, Mario (2022)
    Conference report
    Open Access
    Learning controllers that reproduce legged locomotion in nature has been a long-time goal in robotics and computer graphics. While yielding promising results, recent approaches are not yet flexible enough to be applicable ...
  • Wind prediction using deep learning and high performance computing 

    Manero Font, Jaume; Béjar Alonso, Javier; Cortés García, Claudio Ulises (Springer, 2021)
    Conference report
    Open Access
    Deep Learning Convolutional Neural Networks have been successfully used in many applications. Its versatility lies in reducing the number of parameters to train while maintaining or improving the feature representation ...
  • knowlEdge Project –Concept, methodology and innovations for artificial intelligence in industry 4.0 

    Álvarez Napagao, Sergio; Ashmore, Boki; Barroso Isidoro, Marta; Barrué Subirana, Cristian; Beecks, Christian; Berns, Fabian; Garcia Gasulla, Marta; Jakubiak, Natalia; Megias Montsesinos, Pedro; Sànchez-Marrè, Miquel (Institute of Electrical and Electronics Engineers (IEEE), 2021)
    Conference report
    Open Access
    AI is one of the biggest megatrends towards the 4th industrial revolution. Although these technologies promise business sustainability as well as product and process quality, it seems that the ever-changing market demands, ...
  • Collection, processing and analysis of heterogeneous data coming from Spanish hospitals in the context of COVID-19 

    Barroso Isidoro, Marta; Tormos, Adrián; Pérez Arnal, Raquel Leandra; Álvarez Napagao, Sergio; García Gasulla, Dario (IOS Press, 2021)
    Conference report
    Open Access
    The COVID-19 pandemic has already caused more than 150,000,000 cases worldwide. In Spain this has lead to a massive and simultaneous saturation of all sanitary regions. Coherently, the quick and consistent understanding ...
  • Applying and verifying an explainability method based on policy graphs in the context of reinforcement learning 

    Climent Muñoz, Antoni; Gnatyshak, Dmitry; Álvarez Napagao, Sergio (IOS Press, 2021)
    Conference report
    Open Access
    The advancement on explainability techniques is quite relevant in the field of Reinforcement Learning (RL) and its applications can be beneficial for the development of intelligent agents that are understandable by humans ...
  • The impact of COVID-19 on flight networks 

    Suzumura, Toyotaro; Kanezashi, Hiroki; Dholakia, Mishal; Ishii, Euma; Álvarez Napagao, Sergio; Pérez Arnal, Raquel Leandra; García Gasulla, Dario (Institute of Electrical and Electronics Engineers (IEEE), 2020)
    Conference report
    Open Access
    As COVID-19 transmissions spread worldwide, governments have announced and enforced travel restrictions to prevent further infections. Such restrictions have a direct effect on the volume of international flights among ...
  • Modelling temporal relationships in pseudomonas aeruginosa antimicrobial resistance prediction in intensive care unit 

    Hernández Carnerero, Alvar; Sànchez-Marrè, Miquel; Mora Jiménez, Inmaculada; Soguero Ruiz, Cristina; Martínez Agüero, Sergio; Álvarez Rodríguez, Joaquín (CEUR-WS.org, 2020)
    Conference lecture
    Open Access
    In this paper, the prediction of antimicrobial resistance of Pseudomonas aeruginosa bacteria caused by nosocomial infections in the Intensive Care Unit (ICU) was considered. It was trained a Logistic Regression model using ...

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