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Listar por autor "de Curtò i Díaz, Joaquim"

Mostrando ítems 1-15 de 15

Adaptive Truck Platooning with Drones: A Decentralized Approach for Highway Monitoring

de Curtò, J.; de Zarzà, I.; Cano, Juan-Carlos; Manzoni, Pietro; Tavares De Araujo Cesariny Calafate, Carlos Miguel (MDPI AG, 2023-12)

[EN] The increasing demand for efficient and safe transportation systems has led to the development of autonomous vehicles and vehicle platooning. Truck platooning, in particular, offers numerous benefits, such as reduced ...
Cascading and Ensemble Techniques in Deep Learning

de Zarzà, I.; de Curtò, J.; Hernández-Orallo, Enrique; Tavares De Araujo Cesariny Calafate, Carlos Miguel (MDPI AG, 2023-08)

[EN] In this study, we explore the integration of cascading and ensemble techniques in Deep Learning (DL) to improve prediction accuracy on diabetes data. The primary approach involves creating multiple Neural Networks ...
Detection of glaucoma using three-stage training with EfficientNet

de Zarzà, I.; de Curtò, J.; Tavares De Araujo Cesariny Calafate, Carlos Miguel (Elsevier, 2022-11)

[EN] This paper sets forth a methodology that is based on three-stage-training of a state-of-the-art network architecture previously trained on Imagenet, and iteratively finetuned in three steps; freezing first all layers, ...
Emergent Cooperation and Strategy Adaptation in Multi-Agent Systems: An Extended Coevolutionary Theory with LLMs

de Zarzà, I.; de Curtò, J.; Roig, Gemma; Manzoni, Pietro; Tavares De Araujo Cesariny Calafate, Carlos Miguel (MDPI AG, 2023-06)

[EN] The increasing complexity of Multi-Agent Systems (MASs), coupled with the emergence of Artificial Intelligence (AI) and Large Language Models (LLMs), have highlighted significant gaps in our understanding of the ...
Frontiers of Large Language Models: Empowering Decision Optimization, Scene Understanding, and Summarization Through Advanced Computational Approaches

de Curtò i Díaz, Joaquim (Universitat Politècnica de València, 2024-01-23)

[ES] El advenimiento de los Large Language Models (LLMs) marca una fase transformadora en el campo de la Inteligencia Artificial (IA), significando el cambio hacia sistemas inteligentes y autónomos capaces de una comprensión ...
LLM Adaptive PID Control for B5G Truck Platooning Systems

de Zarzà, I.; de Curtò, J.; Roig, Gemma; Tavares De Araujo Cesariny Calafate, Carlos Miguel (MDPI AG, 2023-07)

[EN] This paper presents an exploration into the capabilities of an adaptive PID controller within the realm of truck platooning operations, situating the inquiry within the context of Cognitive Radio and AI-enhanced 5G ...
LLM Multimodal Traffic Accident Forecasting

de Zarzà, I.; de Curtò, J.; Roig, Gemma; Tavares De Araujo Cesariny Calafate, Carlos Miguel (MDPI AG, 2023-11)

[EN] With the rise in traffic congestion in urban centers, predicting accidents has become paramount for city planning and public safety. This work comprehensively studied the efficacy of modern deep learning (DL) methods ...
LLM-Informed Multi-Armed Bandit Strategies for Non-Stationary Environments

de Curtò, J.; de Zarzà, Irene; Roig, Gemma; Cano, Juan-Carlos; Manzoni, Pietro; Tavares De Araujo Cesariny Calafate, Carlos Miguel (MDPI AG, 2023-07)

[EN] In this paper, we introduce an innovative approach to handling the multi-armed bandit (MAB) problem in non-stationary environments, harnessing the predictive power of large language models (LLMs). With the realization ...
On the applicability of the Hadamard as an input modulator for problems of classification

de Curtò, J.; de Zarzà, I.; Yan, Hong; Tavares De Araujo Cesariny Calafate, Carlos Miguel (Elsevier B.V., 2022-08)

[EN] The library explores the applicability of the Hadamard as an input modulator for problems of classification. It introduces a framework in C++ to use kernel approximates in the mini-batch setting with Stochastic Gradient ...
Optimized Financial Planning: Integrating Individual and Cooperative Budgeting Models with LLM Recommendations

de Zarzà, I.; de Curtò, J.; Roig, Gemma; Tavares De Araujo Cesariny Calafate, Carlos Miguel (MDPI AG, 2024-03)
Optimizing Neural Networks for Imbalanced Data

de Zarzà, I.; de Curtò, J.; Tavares De Araujo Cesariny Calafate, Carlos Miguel (MDPI AG, 2023-06)

[EN] Imbalanced datasets pose pervasive challenges in numerous machine learning (ML) applications, notably in areas such as fraud detection, where fraudulent cases are vastly outnumbered by legitimate transactions. ...
Semantic Scene Understanding with Large Language Models on Unmanned Aerial Vehicles

de Curtò, J.; de Zarzà, I.; Tavares De Araujo Cesariny Calafate, Carlos Miguel (MDPI AG, 2023-02)

[EN] Unmanned Aerial Vehicles (UAVs) are able to provide instantaneous visual cues and a high-level data throughput that could be further leveraged to address complex tasks, such as semantically rich scene understanding. ...
Signature and Log-Signature for the Study of Empirical Distributions Generated with GANs

de Curtò, J.; de Zarzà, I.; Roig, Gemma; Tavares De Araujo Cesariny Calafate, Carlos Miguel (MDPI AG, 2023-05-11)

[EN] In this paper, we address the research gap in efficiently assessing Generative Adversarial Network (GAN) convergence and goodness of fit by introducing the application of the Signature Transform to measure similarity ...
Summarization of Videos with the Signature Transform

de Curtò-I Díaz, Joaquim; de Zarzà-I Cubero, Irene; Roig, Gemma; Tavares De Araujo Cesariny Calafate, Carlos Miguel (MDPI AG, 2023-04)

[EN] This manuscript presents a new benchmark for assessing the quality of visual summaries without the need for human annotators. It is based on the Signature Transform, specifically focusing on the RMSE and the MAE ...
UWB and MB-OFDM for Lunar Rover Navigation and Communication

de Curtò, J.; de Zarzà, I.; Tavares De Araujo Cesariny Calafate, Carlos Miguel (MDPI AG, 2023-09)

[EN] This paper presents a comprehensive study of ultra-wideband (UWB) and multi-band orthogonal frequency-division multiplexing (MB-OFDM) technologies for lunar rover navigation and communication in challenging terrains. ...