Reference health

Motion Imagination EEG Modal Automatic Recognition Based on CNN Network

https://doi.org/10.2139/ssrn.3980352
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18/18 checkable references clean · checked 2026-09-04

Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.

37 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.

The 18 checked references that resolve
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Brain-computer interfaces: where human and machine meet
resolves10.1007/s12559-014-9264-1
A Voting Optimized Strategy Based on ELM for Improving Classification of Motor Imagery BCI Data
resolves10.1007/978-3-642-23187-2_36
EEG Signal Processing for BCI Applications
resolves10.1088/1741-2560/14/1/016003
A novel deep learning approach for classification of EEG motor imagery signals
resolves10.1109/TBME.2004.827072
BCI2000: A General-Purpose Brain-Computer Interface (BCI) System
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Artifact Removal from EEG Signals
resolves10.1016/j.engfracmech.2018.03.010
Artificial intelligence-based machine learning considering flow and temperature of the pipeline for leak early detection using acoustic emission
resolves10.1016/j.wavemoti.2014.01.008
Space–time transformation acoustics
resolves10.1016/j.ins.2020.02.069
TSI: Time series to imaging based model for detecting anomalous energy consumption in smart buildings
resolves10.1504/IJES.2018.091788
A method for electric load data verification and repair in home environment
resolves10.1088/1741-2560/2/4/L02
Characterization of four-class motor imagery EEG data for the BCI-competition 2005
resolves10.1109/TPAMI.2010.125
Convolutional Neural Networks for P300 Detection with Application to Brain-Computer Interfaces
resolves10.1016/j.eswa.2005.04.011
Recurrent neural networks employing Lyapunov exponents for EEG signals classification
resolves10.1016/j.neuroimage.2014.03.048
Restricted Boltzmann machines for neuroimaging: An application in identifying intrinsic networks
resolves10.1016/j.compbiomed.2019.01.013
Cascaded LSTM recurrent neural network for automated sleep stage classification using single-channel EEG signals
resolves10.1016/j.neuron.2012.09.029
Synchronous Oscillatory Neural Ensembles for Rules in the Prefrontal Cortex
resolves10.1109/TLA.2018.8291481
EEG Signals Classification: Motor Imagery for Driving an Intelligent Wheelchair
resolves10.1016/j.eswa.2018.08.031
An end-to-end deep learning approach to MI-EEG signal classification for BCIs
The 37 references without a DOI — listed, not checked
no DOI — not checkedBrain-computer interfacing: An introduction
no DOI — not checkedAutomatic epileptic seizure classification in multichannel EEG time series with linear discriminant analysis
no DOI — not checkedA novel approach of decoding EEG four-class motor imagery tasks via scout ESI and CNN
no DOI — not checkedref5
no DOI — not checkedEEG classification for motor imagery and resting state in BCI applications using multi-class Adaboost extreme learning machine
no DOI — not checkedA Deep Learning Scheme for Motor Imagery Classification based on RestrictedBoltzmann Machines
no DOI — not checkedMotor imagery classification based on deep convolutional neural network and its application in exoskeleton controlled by EEG
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no DOI — not checkedref12
no DOI — not checkedref14
no DOI — not checkedref15
no DOI — not checkedref18
no DOI — not checkedref19
no DOI — not checkedref20
no DOI — not checkedref21
no DOI — not checkedStereo Acoustic Echo Cancellation Employing Frequency-Domain Preprocessing and Adaptive Filter
no DOI — not checkedref24
no DOI — not checkedThe microsoft 2017 conversational speech recognition system
no DOI — not checkedApplication of no-tachometer time synchronous averaging (TSA) and relative signal strengths to localize gear and bearing faults in a helicopter gearbox
no DOI — not checkedImaging Time-Series to Improve Classification and Imputation
no DOI — not checkedEncoding Time Series as Images for Visual Inspection and Classification Using Tiled Convolutional Neural Networks
no DOI — not checkedScaling up dynamic time warping for datamining applications
no DOI — not checkedMart�nez a"Space-time transformation acoustics
no DOI — not checkedA visual encoding model based on deep neural networks and transfer learning for brain activity measured by functional magnetic resonance imaging
no DOI — not checkedVisual and kinesthetic modes affect motor imagery classification in untrained subjects
no DOI — not checkedref41
no DOI — not checkedA Multi-Branch 3D Convolutional Neural Networkfor EEG-Based Motor Imagery Classification
no DOI — not checkedEEG Classification of Motor Imagery Using a Novel Deep Learning Framework
no DOI — not checkedref45
no DOI — not checkedImagenet: A largescale hierarchical image database
no DOI — not checkedref48
no DOI — not checkedTraining very deep networks
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no DOI — not checkedRes2net: A new multi-scale backbone architecture
What this badge says. CiteStamped means the CHECKABLE references of this work were clean at the dated check: each resolved to a known work in a public registry, and none carried a retraction notice at that time. It says nothing about the quality, findings, or importance of the work itself, and nothing about references deposited without a DOI.

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