Ara es mostren els items 1-20 de 316

  • 3D scene reconstruction and understanding from single shot pictures 

    García González, Alfredo (Universitat Politècnica de Catalunya, 2012-09)
    Projecte Final de Màster Oficial
    Accés obert
    Augmented reality mixes computer generated graphics with real imaging using computer vision techniques. However, nowadays, augmented reality is still a very young field of research, and its applications usually involve ...
  • ACon: A learning-based approach to deal with uncertainty in contextual requirements at runtime 

    Knauss, Alessia; Damian, Daniela; Franch Gutiérrez, Javier; Rook, Angela; Müller, Haussi A.; Thomo, Alex (2016-02)
    Article
    Accés obert
    Context: Runtime uncertainty such as unpredictable operational environment and failure of sensors that gather environmental data is a well-known challenge for adaptive systems. Objective: To execute requirements that ...
  • Action rule induction from cause-effect pairs learned through robot-teacher interaction 

    Agostini, Alejandro Gabriel; Celaya Llover, Enric; Torras, Carme; Wörgötter, Florentin (University of Karlsruhe, 2008)
    Text en actes de congrés
    Accés obert
    In this work we propose a decision-making system that efficiently learns behaviors in the form of rules using natural human instructions about cause-effect relations in currently observed situations, avoiding complicated ...
  • Adapting deep neural networks to a low-power environment 

    Mañas Sánchez, Oscar (Universitat Politécnica de Catalunya, 2017)
    Treball Final de Grau
    Accés obert
    These days, working with deep neural networks goes hand in hand with the use of GPUs. Once a deep neural network has been trained for hours, days, or even weeks on a desktop GPU, it is deployed in the field where it runs ...
  • Adaptive distributed mechanism againts flooding network attacks based on machine learning 

    Berral García, Josep Lluís; Poggi Mastrokalo, Nicolas; Alonso López, Javier; Gavaldà Mestre, Ricard; Torres Viñals, Jordi; Parashar, Manish (ACM Press, NY, 2008)
    Text en actes de congrés
    Accés restringit per política de l'editorial
    Adaptive techniques based on machine learning and data mining are gaining relevance in self-management and self- defense for networks and distributed systems. In this paper, we focus on early detection and stopping of ...
  • Adaptive on-line software aging prediction based on machine learning 

    Alonso López, Javier; Torres Viñals, Jordi; Berral García, Josep Lluís; Gavaldà Mestre, Ricard (IEEE Computer Society Publications, 2010)
    Text en actes de congrés
    Accés obert
    The growing complexity of software systems is resulting in an increasing number of software faults. According to the literature, software faults are becoming one of the main sources of unplanned system outages, and have ...
  • Adarules: Learning rules for real-time road-traffic prediction 

    Mena Yedra, Rafael; Gavaldà Mestre, Ricard; Casas Vilaró, Jordi (Elsevier, 2017-12-17)
    Text en actes de congrés
    Accés obert
    Traffic management is being more important than ever, especially in overcrowded big cities with over-pollution problems and with new unprecedented mobility changes. In this scenario, road-traffic prediction plays a key ...
  • A decision making support tool: The resilience management fuzzy controller 

    González Cardenas, Rubén; Nebot Castells, M. Àngela; Múgica Álvarez, Francisco; Vellido Alcacena, Alfredo (Institute of Electrical and Electronics Engineers (IEEE), 2017)
    Text en actes de congrés
    Accés obert
    In this paper a fuzzy controller capable to perform an automated estimation of the period of time necessary to recover a resilience level is proposed. Estimations where made by considering realistic time-dependent action ...
  • Advances in Computational Intelligence and Learning (ESANN 2009) 

    Angulo Bahón, Cecilio; Lee, John A.; Schleif, Frank-Michael (Elsevier Science Direct, 2010-03)
    Article
    Accés restringit per política de l'editorial
  • Advances in machine learning and computational intelligence 

    Schleif, Frank-Michael; Biehl, Michael; Vellido Alcacena, Alfredo (2009-03)
    Article
    Accés restringit per política de l'editorial
  • A fuzzy rule model for high level musical features on automated composition systems 

    Paz Ortiz, Iván; Nebot Castells, M. Àngela; Múgica Álvarez, Francisco; Romero Merino, Enrique (Springer, 2017)
    Capítol de llibre
    Accés restringit per política de l'editorial
    Algorithmic composition systems are now well-understood. However, when they are used for specific tasks like creating material for a part of a piece, it is common to prefer, from all of its possible outputs, those exhibiting ...
  • Algorismes d'aprenentatge per reforç en micro-robots 

    Palma Pérez, Juan (Universitat Politècnica de Catalunya, 2016)
    Projecte/Treball Final de Carrera
    Accés obert
    The aim of this project is the study of reinforcement learning algorithms for micro-robots. It begins with the description of the collective intelligence concept and its main characteristics. Then it presents concepts such ...
  • ALOJA: A framework for benchmarking and predictive analytics in Hadoop deployments 

    Berral García, Josep Lluís; Poggi Mastrokalo, Nicolas; Carrera Pérez, David; Call, Aaron; Reinauer, Rob; Green, Daron (Institute of Electrical and Electronics Engineers (IEEE), 2015-10)
    Article
    Accés obert
    This article presents the ALOJA project and its analytics tools, which leverages machine learning to interpret Big Data benchmark performance data and tuning. ALOJA is part of a long-term collaboration between BSC and ...
  • ALOJA-ML: a framework for automating characterization and knowledge discovery in Hadoop deployments 

    Berral García, Josep Lluís; Poggi, Nicolas; Carrera Pérez, David; Call, Aaaron; Reinauer, Rob; Green, Daron (Association for Computing Machinery (ACM), 2015)
    Text en actes de congrés
    Accés obert
    This article presents ALOJA-Machine Learning (ALOJA-ML) an extension to the ALOJA project that uses machine learning techniques to interpret Hadoop benchmark performance data and performance tuning; here we detail the ...
  • A lower bound for learning distributions generated by probabilistic automata 

    Balle Pigem, Borja de; Castro Rabal, Jorge; Gavaldà Mestre, Ricard (Springer, 2010)
    Text en actes de congrés
    Accés obert
    Known algorithms for learning PDFA can only be shown to run in time polynomial in the so-called distinguishability μ of the target machine, besides the number of states and the usual accuracy and confidence parameters. ...
  • A machine learning approach for layout inference in spreadsheets 

    Koci, Elvis; Thiele, Maik; Romero Moral, Óscar; Lehner, Wolfgang (SciTePress, 2016)
    Text en actes de congrés
    Accés obert
    Spreadsheet applications are one of the most used tools for content generation and presentation in industry and the Web. In spite of this success, there does not exist a comprehensive approach to automatically extract and ...
  • A machine learning approach to the identification of encrypted web traffic 

    Marías Pérez, Rubén (Universitat Politécnica de Catalunya, 2017-06-29)
    Treball Final de Grau
    Accés restringit per acord de confidencialitat
  • A machine learning enabled network planning tool 

    Moysen Cortes, Jessica; Giupponi, Lorenza; Mangues Bafalluy, Josep (Institute of Electrical and Electronics Engineers (IEEE), 2016)
    Text en actes de congrés
    Accés restringit per política de l'editorial
    In the coming years, planning future mobile networks will be infinitely more complex than nowadays. Future networks are expected to present multiple Network Management (NM) challenges to operators, such as managing network ...
  • A machine learning methodology for structural damage classification in structural health monitoring 

    Pozo Montero, Francesc; Tibaduiza Burgos, Diego Alexander; Anaya Vejar, Maribel; Vitola Oyaga, Jaime (2017)
    Text en actes de congrés
    Accés restringit per política de l'editorial
    One of the goals of structural health monitoring (SHM) applications is to determine the presence and the severity of a damage. In some cases, this is an element to forecast the behaviour and take decisions to allocate ...
  • A machine learning pipeline for supporting differentiation of glioblastomas from single brain metastases 

    Mocioiu, Victor; de Barros, Nuno M. Pedrosa; Ortega Martorell, Sandra; Slotboom, Johannes; Knecht, Urspeter; Arús, Carles; Vellido Alcacena, Alfredo; Julià Sapé, Margarida (I6doc.com, 2016)
    Text en actes de congrés
    Accés obert
    Machine learning has provided, over the last decades, tools for knowledge extraction in complex medical domains. Most of these tools, though, are ad hoc solutions and lack the systematic approach that would be required to ...