Home /Research /Convolutional LSTM: A Deep Learning Method for Motion Intention Recognition Based on Spatiotemporal EEG Data

LEARNING

Convolutional LSTM: A Deep Learning Method for Motion Intention Recognition Based on Spatiotemporal EEG Data

Zhijie Fang, Weiqun Wang, Zeng‐Guang Hou

Year: 2019
Citations: 5

Keywords

Computer scienceArtificial intelligenceElectroencephalographyConvolutional neural networkMotion (physics)Pattern recognition (psychology)Speech recognitionNeurosciencePsychology

Convolutional LSTM: A Deep Learning Method for Motion Intention Recognition Based on Spatiotemporal EEG Data

Keywords

Related papers

Statistical Learning Theory

Artificial intelligence: a modern approach

Applied Nonlinear Control

A new optimizer using particle swarm theory