연구동향 분석

Extraction and classification of tempo stimuli from electroencephalography recordings using convolutional recurrent attention model

이기용 김민수 김형국 2021년

논문상세정보
인용/피인용
' Extraction and classification of tempo stimuli from electroencephalography recordings using convolutional recurrent attention model' 의 주제별 논문영향력
논문영향력 선정 방법
논문영향력 요약
주제
  • attention mechanism
  • convolutional recurrent neural network
  • electroencephalography
  • spatiotemporal features
  • tempo stimuli classification
동일주제 총논문수 논문피인용 총횟수 주제별 논문영향력의 평균
73 0

0.0%

' Extraction and classification of tempo stimuli from electroencephalography recordings using convolutional recurrent attention model' 의 참고문헌

  • Using convolutional neural networks to recognize rhythm stimuli from electroencephalography recordings
    S. Stober [2014]
  • Toward studying music cognition with information retrieval techniques: Lessons learned from the OpenMIIR initiative
    S. Stober [2017]
  • Tempo and intensity of pre-task music modulate neural activity during reactive task performance
  • Springer Handbook of Systematic Musicology
    T. Nguyen [2018]
  • Shared mechanisms in perception and imagery of auditory accents
    R. J. Vlek [2011]
  • Open-source practices for music signal processing research: Recommendations for transparent, sustainable, and reproducible audio research
    B. McFee [2019]
  • NMED-T: A tempo-focused dataset of cortical and behavioral responses to naturalistic music
  • Music genre preference and tempo alter alpha and beta waves in human non-musicians
    N. Hurless [2013]
  • Multimodal music information processing and retrieval: Survey and future challenges
  • Long short-term memory
  • Learning phrase representations using RNN encoder-decoder for statistical machine translation
    K. Cho [2014]
  • Electroencephalography based fusion two-dimensional (2D)-convolution neural networks (CNN) model for emotion recognition system
    Y.-H. Kwon [2018]
  • EEG-based emotion recognition using 3D convolutional neural networks
  • EEG frequency-tagging and input–output comparison in rhythm perception
  • DEAP: A database for emotion analysis; using physiological signals
    S. Koelstra [2012]
  • Content-based music information retrieval:Current directions and future challenges
    M. A. Casey [2008]
  • Changes in music tempo entrain movement related brain activity
    I. Daly [2014]
  • Brain beats: Tempo extraction from EEG data
    S. Stober [2016]
  • Attention-based transfer learning for brain-computer interface
    C. Tan [2019]
  • Attention Is All You Need
    A Vaswani [2017]
  • A multimodal view into music’s effect on human neural, physiological, and emotional experience
    T. Greer [2019]
  • A hierarchical bidirectional GRU model with attention for EEG-based emotion classification
    J. X. Chen [2019]
  • A closed-loop braincomputer music interface for continuous affective interaction
    S. Ehrlich [2017]