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Visualitzant Master in Intelligent Interactive Systems​. Master Thesis projects per títol

Visualitzant Master in Intelligent Interactive Systems​. Master Thesis projects per títol

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  • Learning non-linear payoff transformations in multi-agent systems
    Fraxanet, Emma (2021-09)
    The use of Deep Reinforcement Learning methodologies has been successful in recent years in cooperative multi-agent systems. However, this success has been mostly empirical and there is a lack of theoretical understanding ...
  • Learning state representations and Markov models in football analytics
    Soares Afonso, Marielby Mercedes (2019)
    The increasing availability of spatio-temporal data of football matches in recent years has prompted the interest of many clubs in performing automated tactical analysis using machine learning techniques to gain competitive ...
  • Learning to detect Deepfakes: benchmarks and algorithms
    Infante Molina, A. Guillermo (2020-11-13)
    The capabilities of deep-learning tools have led to the emergence of the so-called Deepfakes. These are a type of videos involving a person whose face has been artificially forged in one way or another. These videos poses ...
  • Light transport as an optimal control problem
    Zarza Pujol, Mariano (2021)
    Recently, reinforcement learning (RL) has attracted some attention in the research field of physically-based rendering. This thesis explores a deeper connection between both fields. In particular, we identify the light ...
  • Linguistic emergence in deep neural networks
    Locatelli Metz, Davide (2022)
    Recent work in Emergent Communication has shown that deep neural networks can develop successful strategies of referential communication. Arguably, the extent to which they can do so depends on the properties of the ...
  • Modelling the use of car parks in the province of Barcelona
    Ferrer Sánchez, Josep (2021-07)
    Designing and generating wiser policies for urban systems and infrastructures is a challenge of paramount importance. Today, the cities that present the most successful transport strategies are prioritising the movement ...
  • Multilingual lexical simplification
    Pimienta Castillo, Jorge S. (2021-09)
    This report describes, implement, and evaluate one strategy for text simplification, namely, Lexical Simplification, that aims to reduce the complexity of some words in a sentence. This process is done in two main steps, ...
  • Musculoskeletal abnormality detection on x-ray using transfer learning
    Abreu Dias, Domingo de (2019)
    Radiographic studies are a common technique employed to detect a variety of diseases, in which the detection of musculoskeletal abnormalities has proven to be a crucial task. This thesis proposes the use of deep learning ...
  • Neural architecture search for detection of deepfakes
    Moreno Claver, Jordi (2020)
    DeepFakes has become a social problem by slandering the public image of people. The current and specialized DeepFake detection methods use Hand-Designed Deep Neural Networks as backbone, which requires a lot of designing ...
  • Neural Tree-to-Tree Transduction
    Morales, Cristian (2020-09)
    Graph-structured data is ubiquitous in the field of Natural Language Processing. For instance, directed acyclic graphs are used in semantic and syntactic dependency representations. Thus, several applications in NLP use ...
  • Optimal control using sparse-matrix belief propagation
    Iribarne, Albert (2019)
    The optimal control framework is a mathematical formulation by means of which many decision making problems can be represented and solved by finding optimal policies or controls. We consider the class of optimal control ...
  • Policy gradient methods on a multi-agent game with Kullback-Leibler costs
    Requena Pozo, Borja (2018-07)
    In nature we find all kinds of multi-agent systems sustained upon cooperative behaviours. In this work, we study multi-agent systems by means of the Stag-Hunt game, which presents a conflict between mutual benefit and ...
  • Predicting multi-resistance of bacteria in an Intensive Care Unit
    Hernàndez Carnerero, Àlvar (2020-07)
    This study considers the prediction of “multi-drug” resistance (MDR) of Pseudomonas aeruginosa bacterium caused by nosocomial infections in the Intensive Care Unit (ICU). An ensemble of binary classifiers implemented ...
  • Predicting the use of car parks in the province of Barcelona
    Moreno Esteban, David (2021-07)
    Designing and generating wiser policies for urban systems and infrastructures is a challenge of paramount importance. Today, the cities that present the most successful transport strategies are prioritising the movement ...
  • Predicting user satisfaction to optimize AP selection in WLANs using Random Forests
    Carrascosa Zamacois, Marc (2019)
    Nowadays, it is common to nd WiFi networks that have a central controller connected to all Access Points in the network to both organize them and collect relevant information from them. This creates huge amounts of data ...
  • Predictive gut microbiome analysis for health assessment
    Gil Sorribes, Manel (2023-10-04)
    Personalized medicine is a rapidly evolving field to which many resources have been devoted recently. It represents a paradigm shift from a one-size-fits-all approach to healthcare, focusing instead on tailoring treatments ...
  • Resolution of concurrent planning problems using classical planning
    Furelos Blanco, Daniel (2017-09)
    In this work, we present new approaches for solving multiagent planning and temporal planning problems. These planning forms are two types of concurrent planning, where actions occur in parallel. The methods we propose ...
  • Selecting features of breathing & stability data to predict stress in students
    Fischer, Johannes Simon (2021-07)
    Repeated or long-time exposure to psychological stress is a risk factor for mental and physical health. Especially students are exposed to stress and lacking stress management skills make them particularly vulnerable to ...
  • Speed traffic sign detection on the CARLA simulator using YOLO
    Sánchez Juanola, Martí (2019)
    Research on the self-driving and on the autonomous vehicles field is constantly increasing. The administrations are putting all their efforts to raise awareness among drivers about the responsibility that driving a vehicle ...
  • Task and motion planning: scaling up
    Dalmau Moreno, Magí (2022)
    This master thesis contributes to provide planning capabilities to embodied agents so that they are able to decide what sequence of actions should be taken to solve a given complex problem, involving coupled reasoning ...

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