Now showing items 1-20 of 30

    • A Deep Learning Based Approach to Automated App Testing 

      Llàcer Giner, David (Universitat Politècnica de Catalunya, 2020-09-09)
      Master thesis
      Open Access
      Mobile applications are worldwide extended. We use them for everything, from texting friends to managing our money. This boom has led to the emergence of companies dedicated exclusively to the development of mobile ...
    • An application of explainability methods in reinforcement learning 

      Climent Muñoz, Antoni (Universitat Politècnica de Catalunya, 2020-07-02)
      Bachelor thesis
      Open Access
      La popularidad de los métodos explicativos está aumentando en el contexto de la Inteligencia Artificial y consiste en dar explicaciones inteligibles a modelos complejos. Recientemente, en el contexto del Aprendizaje Reforzado ...
    • Analyzing European Deep-Learning libraries with Industry Standard Benchmark 

      Beduhe Badouh, Asaf (Universitat Politècnica de Catalunya, 2020-10-28)
      Master thesis
      Open Access
      Covenantee:   Barcelona Supercomputing Center
      For the past decade, machine learning (ML) has revolutionized numerous domains in our daily life. Nowadays, deep learning (DL) algorithms are the central focus of modern ML systems. As a result, we are witnessing an ...
    • Aprenentatge profund amb Keras 

      Tena Mensa, Júlia (Universitat Politècnica de Catalunya / Universitat de Barcelona, 2019-06)
      Bachelor thesis
      Open Access
      Aquest treball parteix de la recerca bibliogràfica sobre la intel·ligència artificial, l’aprenentatge automàtic i l’aprenentatge profund. Per començar, en la introducció es troba síntesi de la informació ...
    • Comparing fixed and adaptive computation time for recurrent neural networks 

      Fojo, Daniel; Campos Camunez, Victor; Giró Nieto, Xavier (2018)
      Conference report
      Open Access
      Deep networks commonly perform better than shallow ones, but allocating the proper amount of computation for each particular input sample remains an open problem. This issue is particularly challenging in sequential tasks, ...
    • Coverage model for character-based neural machine translation 

      Kazimi, Mohammad Bashir (Universitat Politècnica de Catalunya, 2017-05)
      Master thesis
      Open Access
      In recent years, Neural Machine Translation (NMT) has achieved state-of-the art performance in translating from a language; source language, to another; target language. However, many of the proposed methods use word ...
    • CVentaur : Una aplicació web per a detecció d’objectes que aprèn de tu 

      Rodríguez Miret, Jan (Universitat Politècnica de Catalunya, 2020-07-13)
      Bachelor thesis
      Open Access
      Durant els darrers anys, el camp de la intel·ligència artificial i l’aprenentatge automàtic ha experimentat un creixement revolucionari gràcies als avenços en àrees com l’aprenentatge profund, i que han obert les portes a ...
    • Deep Learning Techinques for LDPC shortening 

      Auladell i Parellada, Pol (Universitat Politècnica de Catalunya, 2020-08-03)
      Bachelor thesis
      Open Access
      Covenantee:   Karlsruher Institut für Technologie
      The idea of this project is, using Deep Learning (DL) techniques, find a way to shorten a Low-Density Parity-Check (LDPC) code. This is possible since a Bipartite Graph has a similar structure to a artificial neuron system ...
    • Developement of an interactive tool for supervised classification training 

      Aydemir, Mehmet Alp (Universitat Politècnica de Catalunya, 2018-10-30)
      Master thesis
      Restricted access - author's decision
      In recent years, machine learning and computer vision are very cooperative technologies. Combining these two technologies provides learning algorithms in images and videos, and this provides automated extracting meaningful ...
    • Digitally stained confocal microscopy through deep learning 

      Combalia Escudero, Marc; Pérez Ankar, Javiera; García Herrera, Adriana; Alos, Llúcia; Vilaplana Besler, Verónica; Marqués Acosta, Fernando; Puig, Susana; Malvehy, Josep (Microtome Publishing, 2019)
      Conference report
      Open Access
      Specialists have used confocal microscopy in the ex-vivo modality to identify Basal Cell Carcinoma tumors with an overall sensitivity of 96.6% and specificity of 89.2% (Chung et al., 2004). However, this technology hasn’t ...
    • Estudi de viabilitat d'una APP per al control i tractament d'adiccions 

      Andreu Creus, Mireia (Universitat Politècnica de Catalunya, 2020-01)
      Master thesis
      Restricted access - author's decision
      El present Treball de Final de Màster té com a objectiu estudiar la viabilitat tècnica i econòmica del desenvolupament d’una aplicació per al control de les addicions. Primer, per entendre les necessitats d’una aplicació ...
    • KFuji RGB-DS database: Fuji apple multi-modal images for fruit detection with color, depth and range-corrected IR data 

      Gené Mola, Jordi; Vilaplana Besler, Verónica; Rosell Polo, Joan Ramon; Morros Rubió, Josep Ramon; Ruiz Hidalgo, Javier; Gregorio, Eduard (Elsevier, 2019-07-19)
      Article
      Open Access
      This article contains data related to the research article entitle “Multi-modal Deep Learning for Fruit Detection Using RGB-D Cameras and their Radiometric Capabilities” [1]. The development of reliable fruit detection and ...
    • Leishmaniasis parasite segmentation and classification using deep learning 

      Górriz, Marc; Aparicio, Albert; Raventós, Berta; Vilaplana Besler, Verónica; Sayrol Clols, Elisa; López Codina, Daniel (Springer, 2018)
      Conference lecture
      Restricted access - publisher's policy
      Leishmaniasis is considered a neglected disease that causes thousands of deaths annually in some tropical and subtropical countries. There are various techniques to diagnose leishmaniasis of which manual microscopy is ...
    • Machine learning and deep learning for emotion recognition 

      Sisquella Andrés, Joan (Universitat Politècnica de Catalunya, 2019-10-03)
      Master thesis
      Open Access
      Covenantee:   Technische Universität Wien
      Ús de diferents tècniques de deep learning per al reconeixement d'emocions a partir d'imatges i videos. Les diferents tècniques s'apliquen, es valoren i comparen amb l'objectiu de fer-les servir conjuntament en una aplicació ...
    • Monte-Carlo sampling applied to multiple instance learning for histological image classification 

      Combalia, Marc; Vilaplana Besler, Verónica (Springer, 2018)
      Conference lecture
      Restricted access - publisher's policy
      We propose a patch sampling strategy based on a sequential Monte-Carlo method for high resolution image classification in the context of Multiple Instance Learning. When compared with grid sampling and uniform sampling ...
    • Monte-Carlo sampling applied to multiple instance learning for whole slide image classification 

      Combalia, Marc; Vilaplana Besler, Verónica (2018)
      Conference lecture
      Open Access
      In this paper we propose a patch sampling strategy based on sequential Monte-Carlo methods for Whole Slide Image classification in the context of Multiple Instance Learning and show its capability to achieve high generalization ...
    • Paralelización automática del proceso de aprendizaje de una red neuronal Deep Learning 

      García Fuentes, Raúl (Universitat Politécnica de Catalunya, 2020-06-23)
      Bachelor thesis
      Open Access
      Covenantee:   Barcelona Supercomputing Center
      Las redes neuronales y su subcampo, el Deep Learning, han conseguido resultados impresionantes en áreas como la robótica, la visión artificial, el Natural Language Processing (NLP) y el Natural Language Understanding (NLU). ...
    • Reproducing and analyzing adaptive computation time in PyTorch and TensorFlow 

      Fojo Alvarez, Daniel (Universitat Politècnica de Catalunya, 2018-02-06)
      Bachelor thesis
      Open Access
      The complexity of solving a problem can differ greatly to the complexity of posing that problem. Building a Neural Network capable of dynamically adapting to the complexity of the inputs would be a great feat for the machine ...
    • Shot boundary detection using deep convolutional networks 

      Zhao, Chenjia (Universitat Politècnica de Catalunya, 2018-09-07)
      Master thesis
      Open Access
      Shot boundary detection (SBD) is the process of automatically detecting the boundaries between shots in the videos, which is an important pre - processing step for vi deo analysis, such as indexing, browsing, summarization ...
    • Simple vs complex temporal recurrences for video saliency prediction 

      Linardos, Panagiotis; Mohedano, Eva; Nieto, Juan Jose; O'Connor, Noel; Giró Nieto, Xavier; McGuinness, Kevin (2019)
      Conference lecture
      Restricted access - publisher's policy
      This paper investigates modifying an existing neural network architecture for static saliency prediction using two types of recurrences that integrate information from the temporal domain. The first modification is the ...