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Updated: Jun 22, 2026

A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants
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重新思考内在语音解码的方法和算法,并使它们可复制

Foteini Simistira Liwicki1, Vibha Gupta1, Rajkumar Saini1

  • 1Embedded Intelligent Systems LAB, Machine Learning, Department of Computer Science, Electrical and Space Engineering, Luleå University of Technology, 97187 Luleå, Sweden; vibha.gupta@ltu.se (V.G.); rajkumar.saini@ltu.se (R.S.); kanjar.de@ltu.se (K.D.); marcus.liwicki@ltu.se (M.L.).

NeuroSci
|November 1, 2024
PubMed
概括

研究人员使用脑电图 (EEG) 和机器学习解码了内在语言. 这项研究通过共享代码和数据来提高可重现性,在分类元音和单词方面实现了最先进的性能.

关键词:
卷积神经网络 (CNN) 是一种神经网络.大脑计算机接口 (BCI)深度学习是一种深度学习.电脑电图 (EEG) 是一种电脑电图.独立组件分析独立组件分析内在的言语 内在的言语监督学习学习监督学习

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