MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data | Paper Citation Record

Observation 1d608cf6-75ec-4c31-a10d-fd0d0445275a · outbound

This paper cites Exploring the role of primary and supplementary motor areas in simple motor tasks with fnirs.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Exploring the role of primary and supplementary motor areas in simple motor tasks with fnirs

Reference 1

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Observation d82cbf37-181e-4017-b4b8-760b8d10b9bf · outbound

This paper cites Eeg-based neurophysiological in- dices for expert psychomotor performance–a review.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Eeg-based neurophysiological in- dices for expert psychomotor performance–a review

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.613541Z

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Observation 13de29dd-a4ef-4ff7-80d3-ec9038fbd0a1 · outbound

This paper cites The extraction of motion-onset vep bci features based on deep learning and compressed sensing.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data The extraction of motion-onset vep bci features based on deep learning and compressed sensing

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.600912Z

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Observation f6b44240-743f-4aeb-ba9e-b3da899af05a · outbound

This paper cites Dynamics of the eeg power in the frequency and spatial domains during observation and execution of manual movements.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Dynamics of the eeg power in the frequency and spatial domains during observation and execution of manual movements

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.587714Z

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Observation bc7d916e-dc98-44ce-aa34-562665f885b6 · outbound

This paper cites Decoding eeg rhythms during action observation, motor imagery, and execution for standing and sitting.IEEE sensors journal, 20(22):13776–13786, 2020.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Decoding eeg rhythms during action observation, motor imagery, and execution for standing and sitting.IEEE sensors journal, 20(22):13776–13786, 2020

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.574341Z

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Observation 0141b6f2-606e-4bad-9047-2a9b41a7c71b · outbound

This paper cites A deep learning approach for brain computer interaction-motor execution eeg signal classification.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data A deep learning approach for brain computer interaction-motor execution eeg signal classification

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.561353Z

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Observation f1700bff-bd8c-4863-ab8f-cbeaa6f488f3 · outbound

This paper cites On the suitability of near-infrared (nir) systems for next-generation brain–computer interfaces.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data On the suitability of near-infrared (nir) systems for next-generation brain–computer interfaces

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.548808Z

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Observation 2c02a4bf-d3db-42b0-8331-5810e76a83d4 · outbound

This paper cites an unresolved cited work.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-10T21:17:43.537669Z

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Observation ab530126-5475-4744-bd6a-dae2cee6e54d · outbound

This paper cites Real time detection of cognitive load using fnirs: A deep learning approach.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Real time detection of cognitive load using fnirs: A deep learning approach

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.525732Z

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Observation 948c86f5-114a-433e-98f4-81ac7fb812fa · outbound

This paper cites Enhanced drowsiness detection using deep learning: an fnirs study.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Enhanced drowsiness detection using deep learning: an fnirs study

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.512034Z

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Observation 40a5a03c-87bd-4e43-afac-466a699dad0f · outbound

This paper cites A hybrid bci based on eeg and fnirs signals improves the perfor- mance of decoding motor imagery of both force and speed of hand clenching.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data A hybrid bci based on eeg and fnirs signals improves the perfor- mance of decoding motor imagery of both force and speed of hand clenching

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.498530Z

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Observation 4e753cf2-4d0a-49e9-a95a-d525ece18315 · outbound

This paper cites Bimodal data fusion of simultaneous measurements of eeg and fnirs during lower limb movements.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Bimodal data fusion of simultaneous measurements of eeg and fnirs during lower limb movements

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.482713Z

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Observation de5b2af5-7fa2-4576-aab6-a6d539558916 · outbound

This paper cites Identification of lower-limb motor tasks via brain–computer interfaces: a topical overview.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Identification of lower-limb motor tasks via brain–computer interfaces: a topical overview

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.465518Z

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Observation 0d80b3f0-7068-442c-a0aa-8f72544f7999 · outbound

This paper cites Analyzing classification per- formance of fnirs-bci for gait rehabilitation using deep neural networks.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Analyzing classification per- formance of fnirs-bci for gait rehabilitation using deep neural networks

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.452057Z

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Observation 3510fa20-704f-4b63-bba0-c74d8d14b0cf · outbound

This paper cites Decoding multi-class motor imagery and motor execution tasks using rieman- nian geometry algorithms on large eeg datasets.Sensors, 23(11):5051, 2023.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Decoding multi-class motor imagery and motor execution tasks using rieman- nian geometry algorithms on large eeg datasets.Sensors, 23(11):5051, 2023

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.439818Z

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Observation 64659b37-6386-4f80-8aeb-da043495a4e4 · outbound

This paper cites Eeg motor imagery classification with sparse spectrotemporal decomposition and deep learning.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Eeg motor imagery classification with sparse spectrotemporal decomposition and deep learning

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.426833Z

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Observation c12539c6-68ee-4f6a-86a3-1514e1298641 · outbound

This paper cites Transfer learning with data alignment and optimal transport for eeg based mo- tor imagery classification.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Transfer learning with data alignment and optimal transport for eeg based mo- tor imagery classification

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.412411Z

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Observation 93611e90-6a9d-4461-8565-0f9410dbfa4f · outbound

This paper cites A diagonal masking self-attention-based multi-scale network for motor imagery classification.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data A diagonal masking self-attention-based multi-scale network for motor imagery classification

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.397499Z

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Observation ac0f79d2-5839-4c15-916d-c185f33dd732 · outbound

This paper cites Msfnet: A multi-scale space-time frequency fusion network for motor imagery eeg classification.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Msfnet: A multi-scale space-time frequency fusion network for motor imagery eeg classification

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.382620Z

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Observation ae28c830-cd8f-465f-8721-a9e11b6e0821 · outbound

This paper cites Optimal channel selection of multiclass motor imagery classification based on fusion convolutional neural network with attention blocks.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Optimal channel selection of multiclass motor imagery classification based on fusion convolutional neural network with attention blocks

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.368472Z

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Observation df6d1272-3979-4450-b4f4-a4c6e98e142d · outbound

This paper cites Brain-computer interface using neural network Siddhad et al.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Brain-computer interface using neural network Siddhad et al

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.354586Z

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Observation 8ff8518b-4ee9-4966-ac79-438c26cafccb · outbound

This paper cites Motor imagery classification based on eeg sensing with visual and vibrotactile guidance.Sen- sors, 23(11):5064, 2023.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Motor imagery classification based on eeg sensing with visual and vibrotactile guidance.Sen- sors, 23(11):5064, 2023

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.338133Z

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Observation bf15c0f3-29d1-4ce0-ba26-74c73843cc5b · outbound

This paper cites A novel method for classification of multi-class motor imagery tasks based on feature fusion.Neu- roscience Research, 176:40–48, 2022.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data A novel method for classification of multi-class motor imagery tasks based on feature fusion.Neu- roscience Research, 176:40–48, 2022

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.322288Z

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Observation 27440a9d-619f-440e-871f-52e8271f934b · outbound

This paper cites Mar- tins, and Vicente A de Sousa Jr.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Mar- tins, and Vicente A de Sousa Jr

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.298152Z

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Observation aa51d2f8-b822-4f54-b2a8-479d73cf894a · outbound

This paper cites Deep learning for eeg motor imagery classification based on multi-layer cnns feature fusion.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Deep learning for eeg motor imagery classification based on multi-layer cnns feature fusion

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.278098Z

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Observation 055a67ae-2ec7-4bad-97c8-21c8153864d8 · outbound

This paper cites Deep learning for eeg-based motor imagery classification: To- wards enhanced human-machine interaction and assistive robotics.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Deep learning for eeg-based motor imagery classification: To- wards enhanced human-machine interaction and assistive robotics

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.264169Z

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Observation 0756eb1a-6979-42c3-984e-036fde913490 · outbound

This paper cites Eeg clas- sification of motor imagery using a novel deep learning framework.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Eeg clas- sification of motor imagery using a novel deep learning framework

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.248740Z

Source-reported events for the cited work

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Observation aceed98b-b6ab-4062-9f76-d6e2d3c92aad · outbound

This paper cites Hs-cnn: a cnn with hybrid convolution scale for eeg motor imagery classification.Journal of neural engineering, 17(1):016025, 2020.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Hs-cnn: a cnn with hybrid convolution scale for eeg motor imagery classification.Journal of neural engineering, 17(1):016025, 2020

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.235713Z

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Observation 5524a572-2a9f-4163-a4c4-cad182621d4a · outbound

This paper cites Adaptive transfer learning for eeg motor imagery classification with deep con- volutional neural network.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Adaptive transfer learning for eeg motor imagery classification with deep con- volutional neural network

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.221444Z

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Observation 83cc0d18-5ab5-41ac-9362-3ffcd308533e · outbound

This paper cites Deep learning for motor imagery eeg-based classification: A review.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Deep learning for motor imagery eeg-based classification: A review

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.207401Z

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Observation 9c716aae-b8c5-48d7-a92d-820f6dab1441 · outbound

This paper cites A cross-space cnn with customized characteristics for motor imagery eeg classification.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data A cross-space cnn with customized characteristics for motor imagery eeg classification

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.190983Z

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Observation 13010d21-77b5-4398-b801-ba899d9ae477 · outbound

This paper cites Subject-independent deep architecture for eeg-based motor imagery classification.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Subject-independent deep architecture for eeg-based motor imagery classification

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.176557Z

Source-reported events for the cited work

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Observation 7a2331c4-ffaa-456b-b414-b29d349ce540 · outbound

This paper cites Fusion of deep features from 2d-dost of fnirs signals for subject-independent classifi- cation of motor execution tasks.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Fusion of deep features from 2d-dost of fnirs signals for subject-independent classifi- cation of motor execution tasks

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.162268Z

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Observation 94bb2600-451f-4648-b521-fcee82a62fc1 · outbound

This paper cites Functional near-infrared spectroscopy for the clas- sification of motor-related brain activity on the sensor-level.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Functional near-infrared spectroscopy for the clas- sification of motor-related brain activity on the sensor-level

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.147610Z

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Observation 486f42cf-3471-46f7-872c-00518439569f · outbound

This paper cites Classification of motor imagery and execution signals with population-level feature sets: implications for probe design in fnirs based bci.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Classification of motor imagery and execution signals with population-level feature sets: implications for probe design in fnirs based bci

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.130650Z

Source-reported events for the cited work

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Observation 180100d9-e307-4889-b8a8-71de174bfc15 · outbound

This paper cites Single-trial classification of fnirs signals in four directions mo- tor imagery tasks measured from prefrontal cortex.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Single-trial classification of fnirs signals in four directions mo- tor imagery tasks measured from prefrontal cortex

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.110509Z

Source-reported events for the cited work

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Observation a5522ca9-82f9-4618-a633-a1803dfcb440 · outbound

This paper cites An fnirs-based motor imagery bci for als: A subject-specific data-driven approach.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data An fnirs-based motor imagery bci for als: A subject-specific data-driven approach

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.093132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5fd042c8-e5cc-4c36-b792-8a6af032ec87 · outbound

This paper cites Exploiting neurovascular coupling: a bayesian sequential monte carlo approach applied to simulated eeg fnirs data.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Exploiting neurovascular coupling: a bayesian sequential monte carlo approach applied to simulated eeg fnirs data

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.077937Z

Source-reported events for the cited work

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Observation 4eb44d62-3478-4050-8750-e440b4fcf168 · outbound

This paper cites Motor imagery decoding enhancement based on hybrid eeg-fnirs signals.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Motor imagery decoding enhancement based on hybrid eeg-fnirs signals

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.058179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation aadaa6b6-4f59-4ce4-ae5c-8daa73d83152 · outbound

This paper cites Fganet: fnirs-guided at- tention network for hybrid eeg-fnirs brain-computer interfaces.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Fganet: fnirs-guided at- tention network for hybrid eeg-fnirs brain-computer interfaces

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.037459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c2945913-2887-4bf0-b256-70fb65292234 · outbound

This paper cites Hybrid inte- grated wearable patch for brain eeg-fnirs monitoring.Sensors (Basel, Switzer- land), 24(15):4847, 2024.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Hybrid inte- grated wearable patch for brain eeg-fnirs monitoring.Sensors (Basel, Switzer- land), 24(15):4847, 2024

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.021861Z

Source-reported events for the cited work

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Observation 61fbee51-74d9-4873-8187-b85c91b0e8ab · outbound

This paper cites A generalised at- tention mechanism to enhance the accuracy performance of neural networks.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data A generalised at- tention mechanism to enhance the accuracy performance of neural networks

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:43.004882Z

Source-reported events for the cited work

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Observation 0ec98d1c-3773-4303-94b5-18e42bbabbff · outbound

This paper cites Hybrid attention network for epileptic eeg classification.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Hybrid attention network for epileptic eeg classification

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:42.988512Z

Source-reported events for the cited work

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Observation 4c1d9748-50f1-4b89-a4df-bfe59b16354e · outbound

This paper cites A multi-scale fusion convolutional neural network based on attention mechanism for the vi- sualization analysis of eeg signals decoding.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data A multi-scale fusion convolutional neural network based on attention mechanism for the vi- sualization analysis of eeg signals decoding

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:42.974636Z

Source-reported events for the cited work

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Observation cc908cb3-462f-4b25-aa73-9bfa0ce1f724 · outbound

This paper cites an unresolved cited work.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Unresolved cited work

Reference 45

Resolution: unresolved; raw_fallback, observed 2026-08-10T21:17:42.962681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5613bc72-0bf7-4350-ae9f-1d27607b9b7a · outbound

This paper cites Tcja-snn: Temporal-channel joint attention for spiking neural net- works.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Tcja-snn: Temporal-channel joint attention for spiking neural net- works

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:42.947617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f2e42bf4-d857-4241-9a1f-33626dc68d5a · outbound

This paper cites A review on the attention mech- anism of deep learning.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data A review on the attention mech- anism of deep learning

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:42.932779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6d5edeb8-2322-4990-8eb5-32e8f712159b · outbound

This paper cites CAS-ViT: Convolutional Additive Self-attention Vision Transformers for Efficient Mobile Applications.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data CAS-ViT: Convolutional Additive Self-attention Vision Transformers for Efficient Mobile Applications

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-10T21:17:42.639213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c29e9102-1b03-4e0b-8f37-84a213d42878 · outbound

This paper cites Efficientvit: Memory efficient vision transformer with cascaded group attention.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Efficientvit: Memory efficient vision transformer with cascaded group attention

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:42.918293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fc2c758d-0cfc-480d-99e1-340eaa8ce25c · outbound

This paper cites Edgevits: Competing light-weight cnns on mobile devices with vision transformers.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Edgevits: Competing light-weight cnns on mobile devices with vision transformers

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:42.903074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4dfb4167-b5dc-4455-9698-77c55f66b4b5 · outbound

This paper cites SwiftFormer: Efficient Additive Attention for Transformer-based Real-time Mobile Vision Applications.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data SwiftFormer: Efficient Additive Attention for Transformer-based Real-time Mobile Vision Applications

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-10T21:17:42.650646Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d2f8e922-bacb-4cf0-af58-0726269846bc · outbound

This paper cites Deep sparse rectifier neural networks.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Deep sparse rectifier neural networks

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:42.877666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a7be7d8d-f471-4dc4-96b5-fc9a223a4f3c · outbound

This paper cites Hybrid eeg- fnirs asynchronous brain-computer interface for multiple motor tasks.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Hybrid eeg- fnirs asynchronous brain-computer interface for multiple motor tasks

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:42.860613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation cfad10cc-2bdf-4da4-99c7-fe3b4751b6c5 · outbound

This paper cites The modified beer–lambert law revisited.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data The modified beer–lambert law revisited

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:42.845370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 55b5561e-f9cd-47b2-a0d1-d9411390b86d · outbound

This paper cites EEGNet: a compact convolutional neural network for EEG-based brain–computer interfaces.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data EEGNet: a compact convolutional neural network for EEG-based brain–computer interfaces

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:42.828441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8bcbd30f-bffe-4b94-8520-985b7d70e18b · outbound

This paper cites TS- ception: Capturing temporal dynamics and spatial asymmetry from EEG for emotion recognition.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data TS- ception: Capturing temporal dynamics and spatial asymmetry from EEG for emotion recognition

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:42.814900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5351173d-6098-4058-b235-edc31163424c · outbound

This paper cites A convnet for the 2020s.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data A convnet for the 2020s

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:42.800965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b66d0cd0-eb81-4798-957b-fd85bbe6b177 · outbound

This paper cites Neural Networks Meet Neural Activity: Utilizing EEG for Mental Workload Estimation.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Neural Networks Meet Neural Activity: Utilizing EEG for Mental Workload Estimation

Reference 58

Resolution: verified exact; local_arxiv, observed 2026-08-10T21:17:42.734932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8dd31296-491a-4632-97c0-c7c689639895 · outbound

This paper cites Lmda-net: A lightweight multi-dimensional attention network for general eeg-based brain- computer interfaces and interpretability.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Lmda-net: A lightweight multi-dimensional attention network for general eeg-based brain- computer interfaces and interpretability

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:42.786988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 03da8217-b92f-47f0-b789-b0bfa85407cd · outbound

This paper cites Efficacy of transformer networks for classification of eeg data.

MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data Efficacy of transformer networks for classification of eeg data

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:17:42.772770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers