Zobrazeno 1 - 10
of 146
pro vyhledávání: '"Meena, Yogesh"'
Resting-state EEG data in neuroscience research serve as reliable markers for user identification and reveal individual-specific traits. Despite this, the use of resting-state data in EEG classification models is limited. In this work, we propose a f
Externí odkaz:
http://arxiv.org/abs/2411.09789
Brain-computer interfaces (BCIs) enable direct interaction between users and computers by decoding brain signals. This study addresses the challenges of detecting P300 event-related potentials in electroencephalograms (EEGs) and integrating these P30
Externí odkaz:
http://arxiv.org/abs/2410.08561
On-screen keyboard eye-typing systems are limited due to the lack of predictive text and user-centred approaches, resulting in low text entry rates and frequent recalibration. This work proposes integrating the prediction by partial matching (PPM) te
Externí odkaz:
http://arxiv.org/abs/2410.08570
Post-training quantization (PTQ) is a technique used to optimize and reduce the memory footprint and computational requirements of machine learning models. It has been used primarily for neural networks. For Brain-Computer Interfaces (BCI) that are f
Externí odkaz:
http://arxiv.org/abs/2410.07920
Brain-computer interface (BCI) systems facilitate unique communication between humans and computers, benefiting severely disabled individuals. Despite decades of research, BCIs are not fully integrated into clinical and commercial settings. It's cruc
Externí odkaz:
http://arxiv.org/abs/2405.01277
Autor:
Rajpura, Param, Meena, Yogesh Kumar
Decoding EEG during motor imagery is pivotal for the Brain-Computer Interface (BCI) system, influencing its overall performance significantly. As end-to-end data-driven learning methods advance, the challenge lies in balancing model complexity with t
Externí odkaz:
http://arxiv.org/abs/2405.01269
Chest X-ray imaging is a critical diagnostic tool for identifying pulmonary diseases. However, manual interpretation of these images is time-consuming and error-prone. Automated systems utilizing convolutional neural networks (CNNs) have shown promis
Externí odkaz:
http://arxiv.org/abs/2401.00728
This review paper provides an integrated perspective of Explainable Artificial Intelligence techniques applied to Brain-Computer Interfaces. BCIs use predictive models to interpret brain signals for various high-stake applications. However, achieving
Externí odkaz:
http://arxiv.org/abs/2312.13033
Publikováno v:
In Applied Soft Computing December 2024 167 Part B
Publikováno v:
In Information Sciences January 2025 689