Enrique Tomás Martínez Beltrán

Orcid: 0000-0002-5169-2815

According to our database1, Enrique Tomás Martínez Beltrán authored at least 23 papers between 2021 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

2021
2022
2023
2024
2025
0
5
10
1
9
5
3
1
1
2
1

Legend:

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PhD thesis 
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Links

Online presence:

On csauthors.net:

Bibliography

2025
When Brain-Computer Interfaces meet the metaverse: Landscape, demonstrator, trends, challenges, and concerns.
Neurocomputing, 2025

2024
Mitigating communications threats in decentralized federated learning through moving target defense.
Wirel. Networks, November, 2024

Privacy-preserving hierarchical federated learning with biosignals to detect drowsiness while driving.
Neural Comput. Appl., November, 2024

Data fusion in neuromarketing: Multimodal analysis of biosignals, lifecycle stages, current advances, datasets, trends, and challenges.
Inf. Fusion, May, 2024

Studying Drowsiness Detection Performance While Driving Through Scalable Machine Learning Models Using Electroencephalography.
Cogn. Comput., May, 2024

NeuronLab: BCI framework for the study of biosignals.
Neurocomputing, 2024

Fedstellar: A Platform for Decentralized Federated Learning.
Expert Syst. Appl., 2024

Corrigendum to "Fedstellar: A platform for decentralized federated learning" [Expert Syst. Appl. 242 (2024) 122861].
Expert Syst. Appl., 2024

ProFe: Communication-Efficient Decentralized Federated Learning via Distillation and Prototypes.
CoRR, 2024

DART: A Solution for decentralized federated learning model robustness analysis.
Array, 2024

Sentinel: An Aggregation Function to Secure Decentralized Federated Learning.
Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

2023
Opportunities for standardization in emergency scenarios in the European Union.
Int. J. Medical Informatics, November, 2023

Analyzing the impact of Driving tasks when detecting emotions through brain-computer interfaces.
Neural Comput. Appl., April, 2023

Sentinel: An Aggregation Function to Secure Decentralized Federated Learning.
CoRR, 2023

TemporalFED: Detecting Cyberattacks in Industrial Time-Series Data Using Decentralized Federated Learning.
CoRR, 2023

Decentralized Federated Learning: Fundamentals, State of the Art, Frameworks, Trends, and Challenges.
IEEE Commun. Surv. Tutorials, 2023

Stealth Spectrum Sensing Data Falsification Attacks Affecting IoT Spectrum Monitors on the Battlefield.
Proceedings of the IEEE Military Communications Conference, 2023

Fedstellar: A Platform for Training Models in a Privacy-preserving and Decentralized Fashion.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

2022
SAFECAR: A Brain-Computer Interface and intelligent framework to detect drivers' distractions.
Expert Syst. Appl., 2022

Analyzing the Robustness of Decentralized Horizontal and Vertical Federated Learning Architectures in a Non-IID Scenario.
CoRR, 2022

Noise-based cyberattacks generating fake P300 waves in brain-computer interfaces.
Clust. Comput., 2022

Study of P300 Detection Performance by Different P300 Speller Approaches Using Electroencephalography.
Proceedings of the 16th IEEE International Symposium on Medical Information and Communication Technology, 2022

2021
COnVIDa: COVID-19 multidisciplinary data collection and dashboard.
J. Biomed. Informatics, 2021


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