Now showing items 1-20 of 606

  • 3D Bounding box detection from monocular images 

    Catà Villà, Marcel (Universitat Politècnica de Catalunya, 2019-05-08)
    Master thesis
    Open Access
    Object detection is particularly important in robotic applications that require interaction with the environment. Although 2D object detection methods obtain accurate results, these are not enough to provide a complete ...
  • 3D hand reconstruction from RGB-D/RGB video frames in real-time 

    Toda Mas, Aleix (Universitat Politècnica de Catalunya, 2019-04-30)
    Master thesis
    Open Access
    Covenantee:  École polytechnique fédérale de Lausanne
    We present a pipeline able to extract 3D real-world measurements from RGB-D images with high accuracy in real-time. A new method bottom-up multi-person for hand-body pose detection evolved from OpenPifPaf has been presented. ...
  • 3D point cloud correspondences using deep learning 

    Rica Palma, Javier de la (Universitat Politècnica de Catalunya, 2018-05)
    Bachelor thesis
    Open Access
    The main goal of the project is to find correspondences between points in two 3D point clouds using deep learning. A deep learning network is trained to select key points and find correspondences between two point clouds ...
  • 3D point cloud correspondences using graph neural networks 

    Gimenez Arnal, Mario (Universitat Politècnica de Catalunya, 2018-10-17)
    Bachelor thesis
    Open Access
    The purpose of this project is the study of neural networks, their training and application together with the creation of a database appropriate to the system. Specically, the 3D convolutional networks applied to a database ...
  • 3D scene reconstruction and understanding from single shot pictures 

    García González, Alfredo (Universitat Politècnica de Catalunya, 2012-09)
    Master thesis
    Open Access
    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 ...
  • A benchmark for graph neural networks for computer network modeling 

    Carol Bosch, Sergi (Universitat Politècnica de Catalunya, 2019-06-27)
    Master thesis
    Open Access
    Today, network operators still lack functional network models able to make accurate predictions of end-to-end Key Performance Indicators (e.g., delay).This thesis introduces the benchmark for computer network modeling using ...
  • Abstractive text summarization with attention-based mechanism 

    Sanjabi, Nima (Universitat Politècnica de Catalunya, 2018-04)
    Master thesis
    Open Access
    In this work, we explore the evolution of Sequential Neural Models, and their use as a Summarizer System. Transformer is a recently proposed model with a high potential. We experiment and compare their result in abstractive ...
  • Accelerating hyperparameter optimisation with PyCOMPSs 

    Kahira, Albert Njoroge; Bautista Gomez, Leonardo Arturo; Conejero, Javier; Badia Sala, Rosa Maria (Association for Computing Machinery (ACM), 2019)
    Conference report
    Open Access
    Machine Learning applications now span across multiple domains due to the increase in computational power of modern systems. There has been a recent surge in Machine Learning applications in High Performance Computing (HPC) ...
  • 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
    Open Access
    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 recognition in videos 

    Xu, Zineng (Universitat Politècnica de Catalunya, 2018-06-18)
    Master thesis
    Open Access
    In this project, our work can be divided into two parts: RGB-D based action recognition in trimmed videos and temporal action detection in untrimmed videos.
  • 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)
    Conference report
    Open Access
    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 ...
  • A damage classification approach for structural health monitoring using machine learning 

    Tibaduiza Burgos, Diego Alexander; Torres-Arredondo, Miguel Ángel; Vitola Oyaga, Jaime; Anaya Vejar, Maribel; Pozo Montero, Francesc (2018-12-02)
    Article
    Open Access
    Inspection strategies with guided wave-based approaches give to structural health monitoring (SHM) applications several advantages, among them, the possibility of the use of real data from the structure which enables ...
  • Adaptative case-based reasoning: maintenance and learning strategies 

    Nakhjiri, Nariman (Universitat Politècnica de Catalunya, 2018-04)
    Master thesis
    Restricted access - confidentiality agreement
    Covenantee:  Universitat de Barcelona
  • Adapting deep neural networks to a low-power environment 

    Mañas Sánchez, Oscar (Universitat Politècnica de Catalunya, 2017)
    Bachelor thesis
    Open Access
    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)
    Conference report
    Restricted access - publisher's policy
    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)
    Conference report
    Open Access
    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)
    Conference report
    Open Access
    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)
    Conference report
    Open Access
    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
    Restricted access - publisher's policy
  • Advances in machine learning and computational intelligence 

    Schleif, Frank-Michael; Biehl, Michael; Vellido Alcacena, Alfredo (2009-03)
    Article
    Restricted access - publisher's policy