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Paper Citation Record · LEDGER

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation

As of 14 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2607.21654.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2607.21654 v1

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measured 34 of 34 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-01T09:45:02.556396Z

measured 34 of 34 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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34 of 34 outbound references displayed

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Outbound references

Observation 6dff20ff-0257-4f30-8207-5a8079d51ef3 · outbound

This paper cites Applications of higher order statistics in electroencephalography signal processing: A comprehensive survey,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation Applications of higher order statistics in electroencephalography signal processing: A comprehensive survey,

Reference 1

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Observation 316999fd-5521-412b-bd71-d745db4e4c1c · outbound

This paper cites Handbook of psychophysiology,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation Handbook of psychophysiology,

Reference 2

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Observation 5f7fe107-f096-46ae-b3bc-efd0975525a8 · outbound

This paper cites Synaptic mechanisms of thiopental- induced alterations in synchronized cortical activity,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation Synaptic mechanisms of thiopental- induced alterations in synchronized cortical activity,

Reference 3

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Observation 3bc50096-2b7f-43f5-b8cf-b65e5b3fa99b · outbound

This paper cites An overview of independent component analysis and its applications,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation An overview of independent component analysis and its applications,

Reference 4

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Observation d26f9776-83ec-489b-a467-95860f408e5b · outbound

This paper cites Cnn brain label-maker: Computer vision based ica rejection eeg based system architecture,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation Cnn brain label-maker: Computer vision based ica rejection eeg based system architecture,

Reference 5

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Observation 57f35877-6849-410a-9ba5-6969feba96e2 · outbound

This paper cites Iclabel: An automated electroencephalographic independent component classifier, dataset, and website,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation Iclabel: An automated electroencephalographic independent component classifier, dataset, and website,

Reference 6

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Observation 096c3a5b-758f-4d6c-b00b-94ff99a35f1a · outbound

This paper cites Sample entropy enhanced wavelet-ica denoising technique for eye blink artifact removal from scalp eeg dataset,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation Sample entropy enhanced wavelet-ica denoising technique for eye blink artifact removal from scalp eeg dataset,

Reference 7

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Observation 57936de2-3fab-4e15-815e-1c3a647b79ad · outbound

This paper cites Tracking of eeg activity using topographic maps,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation Tracking of eeg activity using topographic maps,

Reference 8

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Observation a53f9018-dd1c-4bc8-96ee-05c91b25cf31 · outbound

This paper cites Reliability of resting-state electrophysiology in fragile x syndrome,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation Reliability of resting-state electrophysiology in fragile x syndrome,

Reference 9

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Observation 5e3a05c5-268c-41bd-aab2-5494a8b5f7d0 · outbound

This paper cites Accuracy of high-density eeg electrode position measurement using an optical scanner compared with the photogrammetry method,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation Accuracy of high-density eeg electrode position measurement using an optical scanner compared with the photogrammetry method,

Reference 10

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Observation 2593ebfe-87af-4496-9af9-f53455e74421 · outbound

This paper cites Compressibility of high-density eeg signals in stroke patients,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation Compressibility of high-density eeg signals in stroke patients,

Reference 11

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Observation a441697a-937b-4618-a5a5-adaecd20d8ef · outbound

This paper cites Utilizing deep learning towards multi-modal bio-sensing and vision-based affective computing,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation Utilizing deep learning towards multi-modal bio-sensing and vision-based affective computing,

Reference 12

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Observation 488dca00-119e-43a6-b054-c46e50776da3 · outbound

This paper cites A review on machine learning for eeg signal processing in bioengineering,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation A review on machine learning for eeg signal processing in bioengineering,

Reference 13

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Observation 32d689c1-d699-45c5-add7-b925816c013b · outbound

This paper cites Predicting age from brain eeg signals—a machine learning approach,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation Predicting age from brain eeg signals—a machine learning approach,

Reference 14

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Observation b5437081-da8a-4d30-9927-c674445202c6 · outbound

This paper cites Deep neural architectures for mapping scalp to intracranial eeg,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation Deep neural architectures for mapping scalp to intracranial eeg,

Reference 15

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Observation d716931e-8d87-4dcd-a221-07feb46f9781 · outbound

This paper cites Eeg signal analysis of patients with epilepsy disorder using machine learning techniques,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation Eeg signal analysis of patients with epilepsy disorder using machine learning techniques,

Reference 16

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Observation 2ec46842-78c1-4916-9db6-8d849215b61c · outbound

This paper cites Automated classification and removal of eeg artifacts with svm and wavelet-ica,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation Automated classification and removal of eeg artifacts with svm and wavelet-ica,

Reference 17

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Observation 512dd5d3-8ac9-4443-9689-dc320c672553 · outbound

This paper cites Classification of eeg signals based on pattern recognition ap- proach,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation Classification of eeg signals based on pattern recognition ap- proach,

Reference 18

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Observation ec0c7f67-3a22-4cdf-a5e0-04b31d074384 · outbound

This paper cites Multimodal data analysis of epileptic eeg and rs-fmri via deep learning and edge computing,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation Multimodal data analysis of epileptic eeg and rs-fmri via deep learning and edge computing,

Reference 19

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Observation e8c8f3e7-0143-4f17-8f4e-c5361dc65729 · outbound

This paper cites Deep learning enabled auto- matic abnormal eeg identification,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation Deep learning enabled auto- matic abnormal eeg identification,

Reference 20

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Observation 811f11d7-6403-48fd-8447-fda569cbd639 · outbound

This paper cites What are decision trees?,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation What are decision trees?,

Reference 21

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Observation f3d0d703-8172-4cd8-b1e8-989bfaa9d25e · outbound

This paper cites Non linear ica and logistic regression for classification of epilepsy from eeg signals,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation Non linear ica and logistic regression for classification of epilepsy from eeg signals,

Reference 22

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Observation 3b6921e3-0e03-4099-97d4-e80ad52dea2e · outbound

This paper cites Deep learning for hybrid eeg-fnirs brain–computer interface: application to motor imagery classification,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation Deep learning for hybrid eeg-fnirs brain–computer interface: application to motor imagery classification,

Reference 23

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Observation ec830355-c5b7-42bb-9448-04a619825024 · outbound

This paper cites Classifying the perceptual interpretations of a bistable image using eeg and artificial neural networks,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation Classifying the perceptual interpretations of a bistable image using eeg and artificial neural networks,

Reference 24

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Observation ecb1740e-8e6f-4c5f-a761-d22d2fc98777 · outbound

This paper cites A cross-sectional evaluation of meditation experience on electroencephalography data by artificial neural network and support vector machine classifiers,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation A cross-sectional evaluation of meditation experience on electroencephalography data by artificial neural network and support vector machine classifiers,

Reference 25

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Observation fc6aed2a-dbeb-45b2-912e-042fae04f7e9 · outbound

This paper cites Epileptic seizure anticipation and localisation of epileptogenic region using eeg signals,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation Epileptic seizure anticipation and localisation of epileptogenic region using eeg signals,

Reference 26

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Observation 9a6ff54b-5eb2-4c9f-b6ef-d6f976a360aa · outbound

This paper cites A machine learning framework involving eeg-based functional connectivity to diagnose major depressive disorder (mdd),.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation A machine learning framework involving eeg-based functional connectivity to diagnose major depressive disorder (mdd),

Reference 27

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Observation ab660f49-465f-4172-9d29-722b470639da · outbound

This paper cites Unsupervised detection and removal of muscle artifacts from scalp eeg recordings using canonical correla- tion analysis, wavelets and random forests,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation Unsupervised detection and removal of muscle artifacts from scalp eeg recordings using canonical correla- tion analysis, wavelets and random forests,

Reference 28

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This paper cites Eeg signal analysis for seizure detection using discrete wavelet transform and random forest,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation Eeg signal analysis for seizure detection using discrete wavelet transform and random forest,

Reference 29

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This paper cites Decoding index finger position from eeg using random forests,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation Decoding index finger position from eeg using random forests,

Reference 30

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Observation ee58290e-652f-4b6e-8f8e-cd8732ea79fe · outbound

This paper cites Detecting dark spot eggs based on cnn googlenet model,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation Detecting dark spot eggs based on cnn googlenet model,

Reference 31

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This paper cites Data augmentation for deep- learning-based electroencephalography,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation Data augmentation for deep- learning-based electroencephalography,

Reference 32

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Observation 7c070661-0b98-4de6-9f6d-52ab17f6c80c · outbound

This paper cites Biased dropout and crossmap dropout: learning towards effective dropout regularization in convolutional neural network,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation Biased dropout and crossmap dropout: learning towards effective dropout regularization in convolutional neural network,

Reference 33

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This paper cites Cole-cnn: Context-learning convolutional neural network with adaptive loss function for lung nodule segmentation,.

Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation Cole-cnn: Context-learning convolutional neural network with adaptive loss function for lung nodule segmentation,

Reference 34

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