Poncelas Vargas, José David(Universitat Politècnica de València, 2024-10-28)
[ES] Este trabajo se enfoca en el análisis y la implementación de técnicas de explicabilidad destinadas a mejorar la comprensión de redes neuronales aplicadas a problemas que implican el procesamiento de imágenes. En primer ...
Pérez-Pelegrí, Manuel; Monmeneu, Jose V.; López-Lereu, María P.; Pérez-Pelegrí, Lucía; Maceira, Alicia M.; Bodi, Vicente; Moratal, David(Elsevier, 2021-09)
[EN] Background and objective: Magnetic resonance imaging is the most reliable imaging technique to assess the heart. More specifically there is great importance in the analysis of the left ventricle, as the main pathologies ...
[EN] Explainable artificial intelligence (XAI) is a growing field that aims to increase the transparency and interpretability of machine learning (ML) models. The aim of this work is to use the categorical properties of ...
Kisilevich, Slava; Herrmann, Markus(Editorial Universitat Politècnica de València, 2023-09-22)
[EN] Marketing Mix Modeling (MMM) employs statistical techniques, typically linear regressions, to assess the impact of advertising expenditure on sales. Despite advancements in statistics and machine learning, the field ...
Schlicht, Ipek Baris; Magnossao de Paula, Angel Felipe(CEUR, 2021-09-24)
[EN] This paper presents a unified user profiling framework to identify hate speech spreaders by processing
their tweets regardless of the language. The framework encodes the tweets with sentence transformers
and applies ...