TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification | Paper Citation Record

Observation 03c92b56-898b-4f20-a1cc-81813d9de914 · outbound

This paper cites Brain computer interfaces, a review,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification Brain computer interfaces, a review,

Reference 1

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Observation fee792fd-cce8-4e7c-9ae9-dbd281eb0ad1 · outbound

This paper cites Brain – Computer Interface Spellers: A Review,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification Brain – Computer Interface Spellers: A Review,

Reference 2

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This paper cites Combining generative adversarial networks and multi-output CNN for motor imagery classification,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification Combining generative adversarial networks and multi-output CNN for motor imagery classification,

Reference 3

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This paper cites Autoreject: Automated artifact rejection for MEG and EEG data,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification Autoreject: Automated artifact rejection for MEG and EEG data,

Reference 4

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This paper cites Generative adversarial networks in EEG analysis: an overview,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification Generative adversarial networks in EEG analysis: an overview,

Reference 5

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This paper cites An Ensemble CNN for Subject-Independent Classification of Motor Imagery-based EEG,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification An Ensemble CNN for Subject-Independent Classification of Motor Imagery-based EEG,

Reference 6

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This paper cites Separated channel convolutional neural network to realize the training free motor imagery BCI systems,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification Separated channel convolutional neural network to realize the training free motor imagery BCI systems,

Reference 7

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This paper cites Cross-Subject EEG Signal Classification with Deep Neural Networks Applied to Motor Imagery,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification Cross-Subject EEG Signal Classification with Deep Neural Networks Applied to Motor Imagery,

Reference 8

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This paper cites Fusion Convolutional Neural Network for Cross-Subject EEG Motor Imagery Classification,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification Fusion Convolutional Neural Network for Cross-Subject EEG Motor Imagery Classification,

Reference 9

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This paper cites Deep Learning Based Inter - subject Continuous Decoding of Motor Imagery for Practical Brain -Computer Interfaces,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification Deep Learning Based Inter - subject Continuous Decoding of Motor Imagery for Practical Brain -Computer Interfaces,

Reference 10

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This paper cites CNN -based Approaches For Cross -Subject Classification in Motor Imagery: From the state -of-the-art to dynamicnet,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification CNN -based Approaches For Cross -Subject Classification in Motor Imagery: From the state -of-the-art to dynamicnet,

Reference 11

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This paper cites Dual Attention Relation Network With Fine-Tuning for Few -Shot EEG Motor Imagery Classification,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification Dual Attention Relation Network With Fine-Tuning for Few -Shot EEG Motor Imagery Classification,

Reference 12

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This paper cites Excellent fine-tuning: From specific-subject classification to cross-task classification for motor imagery,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification Excellent fine-tuning: From specific-subject classification to cross-task classification for motor imagery,

Reference 13

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This paper cites A novel deep learning approach for classification of EEG motor imagery signals,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification A novel deep learning approach for classification of EEG motor imagery signals,

Reference 14

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This paper cites Data augmentation for motor imagery signal classification based on a hybrid neural network,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification Data augmentation for motor imagery signal classification based on a hybrid neural network,

Reference 15

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This paper cites 4 -class mi-eeg signal generation and recognition with cvae-gan,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification 4 -class mi-eeg signal generation and recognition with cvae-gan,

Reference 16

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This paper cites Motor Imagery Classification Enhancement using Generative Adversarial Networks for EEG Spectrum Image Generation,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification Motor Imagery Classification Enhancement using Generative Adversarial Networks for EEG Spectrum Image Generation,

Reference 17

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This paper cites Toward calibration -free motor imagery brain –computer interfaces: a VGG -based convolutional neural network and WGAN approach,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification Toward calibration -free motor imagery brain –computer interfaces: a VGG -based convolutional neural network and WGAN approach,

Reference 18

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This paper cites CNN based classification of motor imaginary using variational mode decomposed EEG -spectrum image,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification CNN based classification of motor imaginary using variational mode decomposed EEG -spectrum image,

Reference 19

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This paper cites EEG-Based Classification of Lower Limb Motor Imagery with STFT and CNN,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification EEG-Based Classification of Lower Limb Motor Imagery with STFT and CNN,

Reference 20

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This paper cites Short -time Fourier transform and embedding method for recurrence quantification analysis of EEG time series,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification Short -time Fourier transform and embedding method for recurrence quantification analysis of EEG time series,

Reference 21

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This paper cites Signal Estimation from Modified Short -Time Fourier Transform,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification Signal Estimation from Modified Short -Time Fourier Transform,

Reference 22

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This paper cites BCI Competition IV.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification BCI Competition IV

Reference 23

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This paper cites Wavelet Transform Time-Frequency Image and Convolutional Network- Based Motor Imagery EEG Classification,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification Wavelet Transform Time-Frequency Image and Convolutional Network- Based Motor Imagery EEG Classification,

Reference 24

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This paper cites BCI Competition 2008-Graz data set A Experimental paradigm,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification BCI Competition 2008-Graz data set A Experimental paradigm,

Reference 25

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This paper cites ‘BCI competition 2008 –Graz data set B’ ,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification ‘BCI competition 2008 –Graz data set B’ ,

Reference 26

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This paper cites Validation of the g.tec Unicorn Hybrid Black wireless EEG system,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification Validation of the g.tec Unicorn Hybrid Black wireless EEG system,

Reference 27

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TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification Generalized digital butterworth filter design,

Reference 28

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This paper cites A compact multi -branch 1D convolutional neural network for EEG-based motor imagery classification,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification A compact multi -branch 1D convolutional neural network for EEG-based motor imagery classification,

Reference 29

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TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification Very Deep Convolutional Networks for Large-Scale Image Recognition

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TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification P-TELU: Parametric Tan Hyperbolic Linear Unit Activation for Deep Neural Networks,

Reference 31

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TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification Improving the efficiency of RMSProp optimizer by utilizing Nestrove in deep learning,

Reference 32

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TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification Cross-Entropy Loss Functions: Theoretical Analysis and Applications

Reference 33

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TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification Understanding and Improving Early Stopping for Learning with Noisy Labels,

Reference 34

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This paper cites MSATNet: multi-scale adaptive transformer network for motor imagery classification,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification MSATNet: multi-scale adaptive transformer network for motor imagery classification,

Reference 35

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This paper cites Analysis of small sample size studies using nonparametric bootstrap test with pooled resampling method,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification Analysis of small sample size studies using nonparametric bootstrap test with pooled resampling method,

Reference 36

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This paper cites Deep Learning for EEG motor imagery classification based on multi -layer CNNs feature fusion,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification Deep Learning for EEG motor imagery classification based on multi -layer CNNs feature fusion,

Reference 37

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This paper cites EISATC -Fusion: Inception Self - Attention Temporal Convolutional Network Fusion for Motor Imagery EEG Decoding,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification EISATC -Fusion: Inception Self - Attention Temporal Convolutional Network Fusion for Motor Imagery EEG Decoding,

Reference 38

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This paper cites Seizure Prediction in EEG Signals Using STFT and Domain Adaptation,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification Seizure Prediction in EEG Signals Using STFT and Domain Adaptation,

Reference 39

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This paper cites EEG classification across sessions and across subjects through transfer learning in motor imagery -based brain-machine interface system,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification EEG classification across sessions and across subjects through transfer learning in motor imagery -based brain-machine interface system,

Reference 40

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This paper cites Improving cross -subject classification performance of motor imagery signals: a data augmentation -focused deep learning framework,.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification Improving cross -subject classification performance of motor imagery signals: a data augmentation -focused deep learning framework,

Reference 41

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TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification Unresolved cited work

Reference 2012

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This paper cites Understanding and Improving Early Stopping for Learning with Noisy Labels.

TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification Understanding and Improving Early Stopping for Learning with Noisy Labels

Reference 2024

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