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Found 4 papers, 2 papers with code
Decentralized Federated Learning: Fundamentals, State of the Art, Frameworks, Trends, and Challenges
In recent years, Federated Learning (FL) has gained relevance in training collaborative models without sharing sensitive data.
Studying Drowsiness Detection Performance while Driving through Scalable Machine Learning Models using Electroencephalography
However, the literature lacks a comprehensive evaluation of drowsiness detection performance using a heterogeneous set of ML algorithms, and it is necessary to study the performance of scalable ML models suitable for groups of subjects.
Data Fusion in Neuromarketing: Multimodal Analysis of Biosignals, Lifecycle Stages, Current Advances, Datasets, Trends, and Challenges
Despite these complexities, there is a lack of literature that adequately collates and organizes the various data sources and the applied processing techniques for the research objectives pursued.
Noise-based cyberattacks generating fake P300 waves in brain–computer interfaces
This work presents and analyzes the impact of four noise-based cyberattacks attempting to generate fake P300 waves in two different phases of a BCI framework.
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