Výsledky vyhledávání - "The ... International Winter Conference on Brain-Computer Interface"

EEG-Transformer: Self-attention from Transformer Architecture for Decoding EEG of Imagined Speech Autor Lee, Young-Eun, Lee, Seo-Hyun

“…Transformers are groundbreaking architectures that have changed a flow of deep learning, and many high-performance models are developing based on transformer…”
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EEG-Based Multimodal Representation Learning for Emotion Recognition Autor Yin, Kang, Shin, Hye-Bin, Li, Dan, Lee, Seong-Whan

“…Multimodal learning has been a popular area of research, yet integrating electroencephalogram (EEG) data poses unique challenges due to its inherent…”
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Identifying Neural Biomarkers of Confirmation Bias Autor Singh, Avinash, Liu, Jia, Voinov, Alexey, Lin, Chin-Teng

“…It has been observed that individuals prefer to favour information that strengthens their beliefs or values, while information that contradicts them causes…”
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Curriculum Learning with Sampling Scheduler for Imbalanced EEG-Based Seizure Detection Autor Choi, WooHyeok, Kim, Jun-Mo, Nam, Hyeonyeong, Kam, Tae-Eui

“…Epileptic seizures pose serious health risks and significantly affect the quality of life for individuals with epilepsy, emphasizing the importance of accurate…”
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Designing an Architecture for a Brain-Computer Interface Operating System: Addressing Neural Input Complexity Autor Choi, Yunseok

“…The unique complexities of neural inputs, such as signal variability, noise sensitivity, and multimodal integration, demand a specialized architecture for…”
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Neurophysiological Analysis in Motor and Sensory Cortices for Improving Motor Imagination Autor Kim, Si-Hyun, Kim, Sung-Jin, Lee, Dae-Hyeok

“…Brain-computer interface (BCI) enables direct communication between the brain and external devices by decoding neural signals, offering potential solutions for…”
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Activity Prediction for Localizing the Events in Imagined Speech EEG Signals Autor Balasubramanian, Arun, Pandey, Kartik, Veer, Gautam, Samanta, Debasis

“…Imagined speech electroencephalogram (EEG) signals are often collected for longer durations than necessary, leading to a difficulty in understanding the…”
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Towards a Network Expansion Approach for Reliable Brain-Computer Interface Autor Lee, Byeong-Hoo, Yin, Kang

“…Robotic arms are increasingly being used in collab-orative environments, requiring an accurate understanding of human intentions to ensure both effectiveness…”
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Towards A Lightweight Deep Learning Framework for Real-Time Vital Sign Prediction with RGB Cameras Autor Kim, Seong-Wook, Park, Hyeong-Yeong, Lee, In-Gyu, Jang, Se-Na, Yu, Seong-Hyun, Oh, Jun-Young, Moon, Gee-Myung, Jeong, Ji-Hoon

“…Remote photoplethysmography (rPPG) is a technology that extracts blood volume pulse (BVP) signals by analyzing the wavelength differences of light reflected…”
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AI in EEG-Based BCI for the Diagnosis of Mild Cognitive Impairment: A Mini Review Autor Zaitsev, Vasilii, Wei, Chun-Shu

“…Mild Cognitive Impairment (MCI) is a condition that often precedes dementia, making early diagnosis critical for delaying cognitive decline…”
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Automated Feature Engineering for Single-Trial EEG and Eye-Tracking Classification in Predictive Text Interfaces Autor Kastrati, Ard, Winters, R. Michael, Djuric, Nemanja, Tashev, Ivan J., Wang, Yu-Te

“…Brain-Computer Interfaces (BCIs) offer a direct connection between the human brain and digital systems, enabling innovative applications. However, realizing…”
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EEG Spectral Analysis in Gray Zone Between Healthy and Insomnia Autor Jo, Ha-Na, Kweon, Young-Seok, Lee, Seo-Hyun

“…This study investigates the sleep characteristics and brain activity of individuals in the gray zone of insomnia, a population that experiences sleep…”
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100 Years of EEG: Unleashing the Brain's Secrets and Motor of Brain-Computer Interface (BCI) Research Autor Kubler, Andrea

“…Electroencephalography (EEG) has come a long way since its discovery, marking over a hundred years of groundbreaking progress. Hans Berger, the scientist…”
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Imagined Speech State Classification for Robust Brain-Computer Interface Autor Ko, Byung-Kwan, Kim, Jun-Young, Lee, Seo-Hyun

“…This study examines the effectiveness of traditional machine learning classifiers versus deep learning models for detecting the imagined speech using…”
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Dataset Refinement for Improving the Generalization Ability of the EEG Decoding Model Autor Kim, Sung-Jin, Lee, Dae-Hyeok, Han, Hyeon-Taek

“…Electroencephalography (EEG) is a generally used neuroimaging approach in brain-computer interfaces due to its non-invasive characteristics and convenience,…”
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Towards Feasible Deep Learning Approach Using EEG for Neurodegenerative Diseases Autor Park, Dogeun, Kim, Ho-Jung, Ju, Young-Gi, Kim, Keun-Tae, Wont, Dong-Ok

“…In this study, we propose the phase space reconstruction (PSR)-based deep learning framework for enhanced detection of frontotemporal dementia (FTD) utilizing…”
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Improving Performance in fNIRS Single Trial Analysis: Multidisciplinary Opportunities and Perspective Autor von Luhmann, Alexander, Middell, Eike, Fischer, Thomas, Tesch, Christian, Siddique, Bilal, Zimmermann, Bernhard B., Moradi, Shakiba, Boas, David A., Muller, Klaus-Robert

“…Advancements in wearable technologies and signal analysis are bringing functional Near-Infrared Spectroscopy (fNIRS) to the forefront of mobile non-invasive…”
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Towards a Neural ODE Generative Model of Cortical Dynamics Autor Douglas, PK

“…Cytoarchitecture studies have revealed that neurons in cortex are not arranged at random, but instead follow a stereotyped pattern - repeated throughout the…”
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Towards Scalable Handwriting Communication via EEG Decoding and Latent Embedding Integration Autor Kim, Jun-Young, Kim, Deok-Seon, Lee, Seo-Hyun

“…In recent years, brain-computer interfaces have made advances in decoding various motor-related tasks, including gesture recognition and movement…”
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Compact Myocardial Infarction Classification for 3-Lead ECG-Based Temporal Convolution with Encoder-Decoder Network Autor Kim, Ray, Choi, Insung, Kim, Gyung Chul, Song, Hee Seok, Lee, Minji, Kim, Yun Kwan

“…Myocardial infarction is one of the leading causes of death worldwide, and early detection is crucial for improving patient outcomes. However, while standard…”
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