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pro vyhledávání: '"Hye Bin An"'
The significant inter-subject variability in electroencephalogram (EEG) signals often leads to knowledge being overwritten as new tasks are introduced in continual EEG decoding. While retraining on the entire dataset with each new input can prevent f
Externí odkaz:
http://arxiv.org/abs/2411.11874
Multimodal learning has been a popular area of research, yet integrating electroencephalogram (EEG) data poses unique challenges due to its inherent variability and limited availability. In this paper, we introduce a novel multimodal framework that a
Externí odkaz:
http://arxiv.org/abs/2411.00822
Computational tomography (CT) provides high-resolution medical imaging, but it can expose patients to high radiation. X-ray scanners have low radiation exposure, but their resolutions are low. This paper proposes a new conditional diffusion model, DX
Externí odkaz:
http://arxiv.org/abs/2409.08850
In the quest for efficient neural network models for neural data interpretation and user intent classification in brain-computer interfaces (BCIs), learning meaningful sparse representations of the underlying neural subspaces is crucial. The present
Externí odkaz:
http://arxiv.org/abs/2312.05828
The application of counterfactual explanation (CE) techniques in the realm of electroencephalography (EEG) classification has been relatively infrequent in contemporary research. In this study, we attempt to introduce and explore a novel non-generati
Externí odkaz:
http://arxiv.org/abs/2312.09456
Neural radiance field (NeRF) is an emerging view synthesis method that samples points in a three-dimensional (3D) space and estimates their existence and color probabilities. The disadvantage of NeRF is that it requires a long training time since it
Externí odkaz:
http://arxiv.org/abs/2310.04152
Publikováno v:
Micro and Nano Systems Letters, Vol 12, Iss 1, Pp 1-10 (2024)
Abstract Simultaneous detection of multiple neurotransmitters and their related activities is crucial for enhancing our understanding of complex neurological mechanisms and disorders. In this study, we developed a flexible, high-sensitivity multi-ele
Externí odkaz:
https://doaj.org/article/a1dfeb3c4721411cb64640cfc2f28611
Autor:
Seo-Ree Choi, Juyong Lee, Yeo-Jin Seo, Ho-Seong Jin, Hye-Bin Ahn, Youyeon Go, Nak-Kyoon Kim, Kyoung-Seok Ryu, Joon-Hwa Lee
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-13 (2024)
Abstract Transcription factors specifically bind to their consensus sequence motifs and regulate transcription efficiency. Transcription factors are also able to non-specifically contact the phosphate backbone of DNA through electrostatic interaction
Externí odkaz:
https://doaj.org/article/20c076a887134e53bb7e7ae074559560
Drowsiness reduces concentration and increases response time, which causes fatal road accidents. Monitoring drivers' drowsiness levels by electroencephalogram (EEG) and taking action may prevent road accidents. EEG signals effectively monitor the dri
Externí odkaz:
http://arxiv.org/abs/2212.13887
Publikováno v:
Frontiers in Surgery, Vol 11 (2024)
ObjectiveWe identified patients who initially did not have a maxillary sinus fungus ball on computed tomography (CT) but developed it on a subsequent CT scan. We assessed potential risk factors for developing a maxillary sinus fungus ball between the
Externí odkaz:
https://doaj.org/article/594debe197d3400d9a82f55995f913d9