Browsing by Subject "Aprenentatge profund"
Now showing items 1-20 of 272
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A closer look at referring expressions for video object segmentation
(2023-01)
Article
Open AccessThe task of Language-guided Video Object Segmentation (LVOS) aims at generating binary masks for an object referred by a linguistic expression. When this expression unambiguously describes an object in the scene, it is ... -
A collaborative statistical actor-critic learning approach for 6G network slicing control
(Institute of Electrical and Electronics Engineers (IEEE), 2021)
Conference lecture
Open AccessArtificial 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
(Elsevier, 2020)
Article
Open AccessCities 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 dataset of microscopic peripheral blood cell images for development of automatic recognition systems
(Elsevier, 2020-06)
Article
Open AccessThis article makes available a dataset that was used for the development of an automatic recognition system of peripheral blood cell images using convolutional neural networks [1]. The dataset contains a total of 17,092 ... -
A deep learning approach for segmentation of red blood cell images and malaria detection
(2020-06-13)
Article
Open AccessMalaria 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
(Universitat Politècnica de Catalunya, 2020-09-09)
Master thesis
Open AccessMobile 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 Deep Learning Based Tool For Ear Training
(Universitat Politècnica de Catalunya, 2023-05-16)
Bachelor thesis
Open AccessL'objectiu principal d'aquest projecte és utilitzar tècniques d'aprenentatge profund per desenvolupar una eina capaç de generar exercicis de dictat melòdic significatius perquè els professors de música i els seus estudiants ... -
A deep learning-based method for uncovering GPCR ligand-induced conformational states using interpretability techniques
(Springer, 2022)
Conference report
Open AccessThere is increasing interest in the development of tools for investigating the protein ligand space. Understanding the underlying mechanisms of G protein-coupled receptors (GPCR) in the ligand-binding process is of particular ... -
A deep q network-based multi-connectivity algorithm for heterogeneous 4G/5G cellular systems
(Springer, 2022)
Conference report
Restricted access - publisher's policyMulti-connectivity, which allows a user equipment to be simultaneously connected to multiple cells from different radio access network nodes that can be from a single or multiple radio access technologies, has emerged as ... -
A deep Q-network-based algorithm for multi-connectivity optimization in heterogeneous cellular-networks †
(2022-08-01)
Article
Open AccessThe use of multi-connectivity has become a useful tool to manage the traffic in heterogeneous cellular network deployments, since it allows a device to be simultaneously connected to multiple cells. The proper exploitation ... -
A dual network for super-resolution and semantic segmentation of sentinel-2 imagery
(Multidisciplinary Digital Publishing Institute (MDPI), 2021-11-12)
Article
Open AccessThere 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
(2021-05-02)
Article
Open AccessMonitoring 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
(Universitat Politècnica de Catalunya, 2021-01-25)
Master thesis
Open Access
Covenantee: Universitat de Barcelona / Universitat Rovira i VirgiliThe 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 Preliminary study of deep learning sensor fusion for pedestrian detection
(Multidisciplinary Digital Publishing Institute (MDPI), 2023-04)
Article
Open AccessMost pedestrian detection methods focus on bounding boxes based on fusing RGB with lidar. These methods do not relate to how the human eye perceives objects in the real world. Furthermore, lidar and vision can have difficulty ... -
A study of Deep Learning techniques for sequence-based problems
(Universitat Politècnica de Catalunya, 2021-10)
Master thesis
Restricted access - author's decisionTransformer 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
(2021-06-07)
Article
Open AccessThe 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 survey of machine and deep learning methods for privacy protection in the Internet of things
(Multidisciplinary Digital Publishing Institute (MDPI), 2023-01-21)
Article
Open AccessRecent advances in hardware and information technology have accelerated the proliferation of smart and interconnected devices facilitating the rapid development of the Internet of Things (IoT). IoT applications and services ... -
A trainable monogenic ConvNet layer robust in front of large contrast changes in image classification
(Institute of Electrical and Electronics Engineers (IEEE), 2021-12-20)
Article
Open AccessConvolutional 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 ... -
Accelerating deep reinforcement learning for digital twin network optimization with evolutionary strategies
(Institute of Electrical and Electronics Engineers (IEEE), 2022)
Conference report
Open AccessThe recent growth of emergent network applications (e.g., satellite networks, vehicular networks) is increasing the complexity of managing modern communication networks. As a result, the community proposed the Digital Twin ... -
Active learning algorithms for multitopic classification
(Universitat Politècnica de Catalunya, 2021-07-08)
Master thesis
Open AccessIn 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 ...
