Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-24T20:29:13.109086Z
Paper Citation Record · LEDGER
An end-to-end (deep) neural network applied to raw EEG, fNIRs and body motion data for data fusion and BCI classification task without any pre-/post-processing
As of 22 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 1 inbound Pith citation observation for arXiv:1907.09523.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T17:13:37.051264Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T17:13:39.775516Z
Reference resolution
23 of 23 outbound references displayed
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- verified fuzzy20
- unresolved3
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 89397089-4464-4dcc-9937-0f49ad817f4b · outbound
This paper cites A brief review on the history of human functional near-infrared spectroscopy (fnirs) development and fields of application.
An end-to-end (deep) neural network applied to raw EEG, fNIRs and body motion data for data fusion and BCI classification task without any pre-/post-processing A brief review on the history of human functional near-infrared spectroscopy (fnirs) development and fields of application
Reference 1
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 3cf9f9af-9141-4491-9a78-e324e3a257b9 · outbound
This paper cites Assessment of the cerebral cortex during motor task behaviours in adults: a systematic review of functional near infrared spectroscopy (fnirs) studies.
An end-to-end (deep) neural network applied to raw EEG, fNIRs and body motion data for data fusion and BCI classification task without any pre-/post-processing Assessment of the cerebral cortex during motor task behaviours in adults: a systematic review of functional near infrared spectroscopy (fnirs) studies
Reference 2
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 3b1527e2-25fa-451c-abb3-659744d8bfb0 · outbound
This paper cites Near infrared spectroscopy (nirs): a new tool to study hemodynamic changes during activation of brain function in human adults.
An end-to-end (deep) neural network applied to raw EEG, fNIRs and body motion data for data fusion and BCI classification task without any pre-/post-processing Near infrared spectroscopy (nirs): a new tool to study hemodynamic changes during activation of brain function in human adults
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-24T20:29:53.461953Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 09b0f74b-a825-4444-b1ba-82d8321b2139 · outbound
This paper cites Spatio-temporal differ- ences in brain oxygenation between movement execution and imagery: a multichannel near-infrared spectroscopy study.
An end-to-end (deep) neural network applied to raw EEG, fNIRs and body motion data for data fusion and BCI classification task without any pre-/post-processing Spatio-temporal differ- ences in brain oxygenation between movement execution and imagery: a multichannel near-infrared spectroscopy study
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-24T20:29:53.491990Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 28a26397-7630-4cd0-883b-32fc1140ec60 · outbound
This paper cites an unresolved cited work.
An end-to-end (deep) neural network applied to raw EEG, fNIRs and body motion data for data fusion and BCI classification task without any pre-/post-processing Unresolved cited work
Reference 5
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 4f441d5e-0d83-4e26-8f3c-ea67a927c1b7 · outbound
This paper cites Convolutional neural network with em- bedded fourier transform for eeg classification.
An end-to-end (deep) neural network applied to raw EEG, fNIRs and body motion data for data fusion and BCI classification task without any pre-/post-processing Convolutional neural network with em- bedded fourier transform for eeg classification
Reference 6
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation d1c10edc-f4f4-4c04-858c-b35eb880c190 · outbound
This paper cites 19th International Conference on.
An end-to-end (deep) neural network applied to raw EEG, fNIRs and body motion data for data fusion and BCI classification task without any pre-/post-processing 19th International Conference on
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-24T20:29:53.495553Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation b321828f-e1e0-4383-8bb3-b939f72623ab · outbound
This paper cites Convolutional neural networks for event-related potential detection: impact of the architecture.
An end-to-end (deep) neural network applied to raw EEG, fNIRs and body motion data for data fusion and BCI classification task without any pre-/post-processing Convolutional neural networks for event-related potential detection: impact of the architecture
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-24T20:29:53.481077Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation df73ab37-4e80-47d2-a939-6c9561f72d81 · outbound
This paper cites A time–frequency convolutional neural network for the offline classification of steady-state visual evoked potential responses.
An end-to-end (deep) neural network applied to raw EEG, fNIRs and body motion data for data fusion and BCI classification task without any pre-/post-processing A time–frequency convolutional neural network for the offline classification of steady-state visual evoked potential responses
Reference 9
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation cf9f8f34-9f20-4966-a2ca-912b9183ed1d · outbound
This paper cites Trakoolwilaiwan, B.
An end-to-end (deep) neural network applied to raw EEG, fNIRs and body motion data for data fusion and BCI classification task without any pre-/post-processing Trakoolwilaiwan, B
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-24T20:29:53.522199Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 9c9b37b2-af26-41c7-b1a8-8c0eb10466c5 · outbound
This paper cites Brain–computer inter- face using a simplified functional near-infrared spectroscopy system.
An end-to-end (deep) neural network applied to raw EEG, fNIRs and body motion data for data fusion and BCI classification task without any pre-/post-processing Brain–computer inter- face using a simplified functional near-infrared spectroscopy system
Reference 11
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 74140f58-caa4-4f07-8126-261a4d13810c · outbound
This paper cites fnirs-based brain-computer interfaces: a review.
An end-to-end (deep) neural network applied to raw EEG, fNIRs and body motion data for data fusion and BCI classification task without any pre-/post-processing fnirs-based brain-computer interfaces: a review
Reference 12
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 2f81e890-48c2-47da-9326-c9251ad11afa · outbound
This paper cites Functional near infrared spectroscope for cognition brain tasks by wavelets analysis and neural networks.
An end-to-end (deep) neural network applied to raw EEG, fNIRs and body motion data for data fusion and BCI classification task without any pre-/post-processing Functional near infrared spectroscope for cognition brain tasks by wavelets analysis and neural networks
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-24T20:29:53.518621Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 206b9d2d-582e-48af-8aa4-a4d0596daf69 · outbound
This paper cites Deep learning for hybrid eeg-fnirs brain–computer interface: application to motor imagery classification.
An end-to-end (deep) neural network applied to raw EEG, fNIRs and body motion data for data fusion and BCI classification task without any pre-/post-processing Deep learning for hybrid eeg-fnirs brain–computer interface: application to motor imagery classification
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-24T20:29:53.507804Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation dabcc5a6-3e70-4db7-bb71-a1f39b7fe590 · outbound
This paper cites Investigating deep learning for fnirs based bci.
An end-to-end (deep) neural network applied to raw EEG, fNIRs and body motion data for data fusion and BCI classification task without any pre-/post-processing Investigating deep learning for fnirs based bci
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-24T20:29:53.515060Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 288fd611-19c2-4b3f-8206-83269487f017 · outbound
This paper cites Analyzing brain functions by subject classification of functional near- infrared spectroscopy data using convolutional neural networks analy- sis.
An end-to-end (deep) neural network applied to raw EEG, fNIRs and body motion data for data fusion and BCI classification task without any pre-/post-processing Analyzing brain functions by subject classification of functional near- infrared spectroscopy data using convolutional neural networks analy- sis
Reference 16
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation a38b6d94-f60c-4453-aa2f-efd3204ffe12 · outbound
This paper cites Validating deep neural networks for online decoding of motor imagery movements from eeg signals.
An end-to-end (deep) neural network applied to raw EEG, fNIRs and body motion data for data fusion and BCI classification task without any pre-/post-processing Validating deep neural networks for online decoding of motor imagery movements from eeg signals
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-24T20:29:53.526000Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 165cf359-c17f-43ce-b212-82c4a5b84cd1 · outbound
This paper cites A deep learning mi-eeg classification model for bcis.
An end-to-end (deep) neural network applied to raw EEG, fNIRs and body motion data for data fusion and BCI classification task without any pre-/post-processing A deep learning mi-eeg classification model for bcis
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-24T20:29:53.445943Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 485ed192-bab7-4365-ac6e-e2fae66f34cd · outbound
This paper cites fnirs-based brain–computer interface using deep neural networks for classifying the mental state of drivers.
An end-to-end (deep) neural network applied to raw EEG, fNIRs and body motion data for data fusion and BCI classification task without any pre-/post-processing fnirs-based brain–computer interface using deep neural networks for classifying the mental state of drivers
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-24T20:29:53.466033Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 7aec39a5-8f93-4986-b599-7be1f04db8ab · outbound
This paper cites an unresolved cited work.
An end-to-end (deep) neural network applied to raw EEG, fNIRs and body motion data for data fusion and BCI classification task without any pre-/post-processing Unresolved cited work
Reference 20
- Resolution
- unresolved
- raw_fallback, observed 2026-05-24T20:29:53.469535Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation cff493fb-3f3c-4cd8-99a0-c8e59b1b3663 · outbound
This paper cites an unresolved cited work.
An end-to-end (deep) neural network applied to raw EEG, fNIRs and body motion data for data fusion and BCI classification task without any pre-/post-processing Unresolved cited work
Reference 21
- Resolution
- unresolved
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation df2348da-3e92-4772-8efa-c38e54a2a3c9 · outbound
This paper cites Interpretation of convolutional neural networks for speech spectrogram regression from intracranial recordings.
An end-to-end (deep) neural network applied to raw EEG, fNIRs and body motion data for data fusion and BCI classification task without any pre-/post-processing Interpretation of convolutional neural networks for speech spectrogram regression from intracranial recordings
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-24T20:29:53.442406Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation c102a9b1-dd96-42aa-9cd3-4df246a12674 · outbound
This paper cites Eeg-based user identification system us- ing 1d-convolutional long short-term memory neural networks.
An end-to-end (deep) neural network applied to raw EEG, fNIRs and body motion data for data fusion and BCI classification task without any pre-/post-processing Eeg-based user identification system us- ing 1d-convolutional long short-term memory neural networks
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-24T20:29:53.450839Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Pith citing papers
Observation 299071e2-b1ad-4f3f-afeb-04b2ea2c574b · inbound
Toward Improving fNIRS Classification: A Study on Activation Functions in Deep Neural Architectures cites this paper.
Toward Improving fNIRS Classification: A Study on Activation Functions in Deep Neural Architectures An end-to-end (deep) neural network applied to raw EEG, fNIRs and body motion data for data fusion and BCI classification task without any pre-/post-processing
Reference 10
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-06T17:13:40.005035Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.