Titlebook: Brain Informatics; International Confer Yi Zeng,Yong He,Qingming Luo Conference proceedings 2017 Springer International Publishing AG 2017

退缩

书目名称Brain Informatics影响因子(影响力)




书目名称Brain Informatics影响因子(影响力)学科排名




书目名称Brain Informatics网络公开度




书目名称Brain Informatics网络公开度学科排名




书目名称Brain Informatics被引频次




书目名称Brain Informatics被引频次学科排名




书目名称Brain Informatics年度引用




书目名称Brain Informatics年度引用学科排名




书目名称Brain Informatics读者反馈




书目名称Brain Informatics读者反馈学科排名

cumber

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enumaerate

RAFF

Operating the System, Version 2,g and expression of affective pattern, and then improve the accuracy of recognition. The accuracy of the proposed multi-layer EEG-ER system is compared with various feature extraction methods. For analysis results, average and maximum classification rates of 64% and 67.0% were obtained for arousal and 66.6% and 76.0% for valence.

Adherent

Learning Music Emotions via Quantum Convolutional Neural Networkms as well as the state-of-the-art in the task of music emotion classification. Moreover, we provide demonstration experiment to explain the good performance of the proposed technique from the perspective of physics and psychology.

Handedness

EEG-Based Emotion Recognition via Fast and Robust Feature Smoothingesults on the well-known DEAP dataset demonstrate the effectiveness of our approach. Comparing to other studies on the same dataset, ours achieves the shortest feature processing time and the highest classification accuracy on emotion recognition in the valence-arousal quadrant space.

Urea508

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