Cargando…
SAST-GCN: Segmentation Adaptive Spatial Temporal-Graph Convolutional Network for P3-Based Video Target Detection
Detecting video-induced P3 is crucial to building the video target detection system based on the brain-computer interface. However, studies have shown that the brain response patterns corresponding to video-induced P3 are dynamic and determined by the interaction of multiple brain regions. This pape...
Autores principales: | Lu, Runnan, Zeng, Ying, Zhang, Rongkai, Yan, Bin, Tong, Li |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9201684/ https://www.ncbi.nlm.nih.gov/pubmed/35720707 http://dx.doi.org/10.3389/fnins.2022.913027 |
Ejemplares similares
-
Spatial-Temporal Attention Mechanism and Graph Convolutional Networks for Destination Prediction
por: Li, Cong, et al.
Publicado: (2022) -
Sparse Spatial-Temporal Emotion Graph Convolutional Network for Video Emotion Recognition
por: Liu, Xiaodong, et al.
Publicado: (2022) -
MD-GCN: A Multi-Scale Temporal Dual Graph Convolution Network for Traffic Flow Prediction
por: Huang, Xiaohui, et al.
Publicado: (2023) -
CID-GCN: An Effective Graph Convolutional Networks for Chemical-Induced Disease Relation Extraction
por: Zeng, Daojian, et al.
Publicado: (2021) -
Linking Multi-Layer Dynamical GCN With Style-Based Recalibration CNN for EEG-Based Emotion Recognition
por: Bao, Guangcheng, et al.
Publicado: (2022)