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Spatiotemporal Pooling on Appropriate Topological Maps Represented as
  Two-Dimensional Images for EEG Classification

Spatiotemporal Pooling on Appropriate Topological Maps Represented as Two-Dimensional Images for EEG Classification

7 March 2024
Takuto Fukushima
Ryusuke Miyamoto
ArXivPDFHTML

Papers citing "Spatiotemporal Pooling on Appropriate Topological Maps Represented as Two-Dimensional Images for EEG Classification"

3 / 3 papers shown
Title
BENDR: using transformers and a contrastive self-supervised learning
  task to learn from massive amounts of EEG data
BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG data
Demetres Kostas
Stephane Aroca-Ouellette
Frank Rudzicz
SSL
49
203
0
28 Jan 2021
Pre-training without Natural Images
Pre-training without Natural Images
Hirokatsu Kataoka
Kazushige Okayasu
Asato Matsumoto
Eisuke Yamagata
Ryosuke Yamada
Nakamasa Inoue
Akio Nakamura
Y. Satoh
81
117
0
21 Jan 2021
ImageNet Large Scale Visual Recognition Challenge
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky
Jia Deng
Hao Su
J. Krause
S. Satheesh
...
A. Karpathy
A. Khosla
Michael S. Bernstein
Alexander C. Berg
Li Fei-Fei
VLM
ObjD
298
39,238
0
01 Sep 2014
1