Now showing items 1-20 of 163

    • A collaborative statistical actor-critic learning approach for 6G network slicing control 

      Rezazadeh, Farhad; Chergui, Hatim; Blanco Botana, Luis; Alonso Zárate, Luis Gonzaga; Verikoukis, Christos (Institute of Electrical and Electronics Engineers (IEEE), 2021)
      Conference lecture
      Open Access
      Artificial intelligence (AI)-driven zero-touch massive network slicing is envisioned to be a disruptive technology in beyond 5G (B5G)/6G, where tenancy would be extended to the final consumer in the form of advanced digital ...
    • A comparison of deep learning methods for urban traffic forecasting using floating car data 

      Vázquez Giménez, Juan José; Arjona Martínez, Jamie; Linares Herreros, María Paz; Casanovas Garcia, Josep (Elsevier, 2020)
      Article
      Open Access
      Cities today must address the challenge of sustainable mobility, and traffic state forecasting plays a key role in mitigating traffic congestion in urban areas. For example, predicting path travel time is a crucial issue ...
    • A deep learning approach for segmentation of red blood cell images and malaria detection 

      Delgado Ortet, Maria; Molina Borrás, Ángel; Alférez Baquero, Edwin Santiago; Rodellar Benedé, José; Merino González, Anna (2020-06-13)
      Article
      Open Access
      Malaria is an endemic life-threating disease caused by the unicellular protozoan parasites of the genus Plasmodium. Confirming the presence of parasites early in all malaria cases ensures species-specific antimalarial ...
    • 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 ...
    • A dual network for super-resolution and semantic segmentation of sentinel-2 imagery 

      Abadal Lloret, Sauc; Salgueiro Romero, Luis Fernando; Marcello Ruiz, Javier; Vilaplana Besler, Verónica (Multidisciplinary Digital Publishing Institute (MDPI), 2021-11-12)
      Article
      Open Access
      There is a growing interest in the development of automated data processing workflows that provide reliable, high spatial resolution land cover maps. However, high-resolution remote sensing images are not always affordable. ...
    • A novel deep learning-based diagnosis method applied to power quality disturbances 

      González Abreu, Artvin Darién; Delgado Prieto, Miquel; Osornio Rios, Roque A.; Saucedo Dorantes, Juan Jose; Romero Troncoso, René de Jesús (2021-05-02)
      Article
      Open Access
      Monitoring electrical power quality has become a priority in the industrial sector background: avoiding unwanted effects that affect the whole performance at industrial facilities is an aim. The lack of commercial equipment ...
    • A pipeline for large raw text preprocessing and model training of language models at scale 

      Armengol Estapé, Jordi (Universitat Politècnica de Catalunya, 2021-01-25)
      Master thesis
      Open Access
      Covenantee:   Universitat de Barcelona / Universitat Rovira i Virgili
      The advent of Transformer-based (i.e., based on self-attention architectures) language models has revolutionized the entire field of Natural Language Processing (NLP). Once pre-trained on large, unlabelled corpora, we can ...
    • A study of Deep Learning techniques for sequence-based problems 

      Quintana Valenzuela, Diego (Universitat Politècnica de Catalunya, 2021-10)
      Master thesis
      Open Access
      Transformer Networks are a new type of Deep Learning architecture first introduced in 2017. By only applying attention mechanisms, the transformer network can model relations between text sequences that outperformed other ...
    • A survey of deep learning techniques for cybersecurity in mobile networks 

      Rodríguez Luna, Eva; Otero Calviño, Beatriz; Gutiérrez Escobar, Norma; Canal Corretger, Ramon (2021-06-07)
      Article
      Open Access
      The widespread use of mobile devices, as well as the increasing popularity of mobile services has raised serious cybersecurity challenges. In the last years, the number of cyberattacks has grown dramatically, as well as ...
    • A trainable monogenic ConvNet layer robust in front of large contrast changes in image classification 

      Moya Sánchez, Eduardo Ulises; Xambó Descamps, Sebastián; Sánchez-Pérez, Abraham; Salazar Colores, Sebastián; Cortés García, Claudio Ulises (Institute of Electrical and Electronics Engineers (IEEE), 2021-12-20)
      Article
      Open Access
      Convolutional Neural Networks (ConvNets) at present achieve remarkable performance in image classification tasks. However, current ConvNets cannot guarantee the capabilities of the mammalian visual systems such as invariance ...
    • Active learning algorithms for multitopic classification 

      Bonafonte Pardàs, Guillem (Universitat Politècnica de Catalunya, 2021-07-08)
      Master thesis
      Open Access
      In this master thesis we develop a model that surpasses previous studies to be able to detect cyberbullying and other disorders that are a common behaviour in teenagers. We analyze short sentences in social media with new ...
    • 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 ...
    • An approach to traffic flow prediction with stacked autoencoders 

      Garcia Vera, Pau (Universitat Politècnica de Catalunya, 2018-06)
      Bachelor thesis
      Restricted access - author's decision
      Covenantee:   Tong ji da xue
      Amid the flourishing world of machine learning and deep learning, many new ideas and projects can sprout, thanks to the interesting capabilities offered by this set of techniques, all focused on studying patterns in copious ...
    • An autoencoder-based Solution for IQ constellation analysis 

      Morales López, Javier Roman (Universitat Politècnica de Catalunya, 2021-09-09)
      Bachelor thesis
      Open Access
      The continuous advances in technology and globalisation of humanity has made the use of communications an essential part of human lives. Nowadays, the advances in this field and the huge amount of data, structured and ...
    • An oracle for guiding large-scale model/hybrid parallel training of convolutional neural networks 

      Njoroge Kahira, Albert; Nguyen, Truong Thao; Bautista Gomez, Leonardo Arturo; Takano, Ryousei; Badia Sala, Rosa Maria; Wahib, Mohamed (European Network of Excellence on High Performance and Embedded Architecture and Compilation (HiPEAC), 2021)
      Conference lecture
      Open Access
      Deep Neural Network (DNN) frameworks use distributed training to enable faster time to convergence and alleviate memory capacity limitations when training large models and/or using high dimension inputs. With the steady ...
    • Analysis of pet behaviour using computer vision 

      Lumbreras Navarro, Raúl (Universitat Politècnica de Catalunya, 2022-06-29)
      Bachelor thesis
      Open Access
      Que fa la teva mascota quan no ets a casa? Amb tècniques de l'estat de l'art en detecció d'objectes i reconeixement d'objectes, un sistema de vigilància capaç de detectar mascotes és possible de fer. No tan sols això, sinó ...
    • 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 ...
    • Anomaly detection in electromechanical systems by means of deep-autoencoder 

      Arellano Espitia, Francisco; Delgado Prieto, Miquel; Martínez Viol, Víctor; Fernández Sobrino, Ángel; Osornio Rios, Roque A. (Institute of Electrical and Electronics Engineers (IEEE), 2021)
      Conference report
      Open Access
      Anomaly detection in manufacturing processes is one of the main concerns in the new era of the Industry 4.0 framework. The detection of uncharacterized events represents a major challenge within the operation monitoring ...
    • Anti-spoofing mechanisms in face recognition 

      Bové Escribano, Sergi (Universitat Politècnica de Catalunya, 2020-09-02)
      Master thesis
      Restricted access - author's decision
      Covenantee:   Slovenská technická univerzita v Bratislave
      The objective of this work is to design and implement a pupil detection solution to be used as part of an anti-spoofing mechanism in face recognition. This is intended to improve the security and reliability of face ...
    • Application of deep learning upscaling technologies in cloud gaming solutions 

      Carles Ramon, Efren (Universitat Politècnica de Catalunya, 2022-06-30)
      Bachelor thesis
      Open Access
      Durant tota la seva història, la indústria dels videojocs ha vist com any rere any els requeriments hardware de les entregues més populars del mercat augmentaven amb cada nova sortida. Això, juntament amb l'encariment dels ...