paper
-with-
me
Papers
Browse State-of-the-Art
Datasets
Methods
AI Agents
Trends
Digest
🌙
Within-Session Motor Imagery (all classes)
벤치마크
Within-Session Motor Imagery (all classes) on
Weibo2014 MOABB
64개 결과 ·
⬇ CSV
·
JSON
Accuracy
17.95
29.56
41.17
52.77
64.38
2024-04
2026-09
ACM + TS + SVM — 64.3835718 (2024-04-03)
TS + EL — 63.840714199999994 (2024-04-03)
TS + LR — 62.762142 (2024-04-03)
TS + SVM — 61.469286499999995 (2024-04-03)
FgMDM — 56.9400009 (2024-04-03)
ShallowConvNet — 48.9364276 (2024-04-03)
FBCSP + SVM — 45.212857299999996 (2024-04-03)
CSP + SVM — 44.0792858 (2024-04-03)
CSP + LDA — 39.4492859 (2024-04-03)
DLCSPauto + shLDA — 38.8442857 (2024-04-03)
EEGNet-8,2 — 35.3514286 (2024-04-03)
MDM — 33.4078569 (2024-04-03)
EEGNeX — 30.215714 (2024-04-03)
EEGITNet — 25.7807146 (2024-04-03)
DeepConvNet — 24.1678569 (2024-04-03)
EEGTCNet — 17.9464288 (2024-04-03)
ACM + TS + SVM — 64.3835718 (2024-04-03)
TS + EL — 63.840714199999994 (2024-04-03)
TS + LR — 62.762142 (2024-04-03)
TS + SVM — 61.469286499999995 (2024-04-03)
FgMDM — 56.9400009 (2024-04-03)
ShallowConvNet — 48.9364276 (2024-04-03)
FBCSP + SVM — 45.212857299999996 (2024-04-03)
CSP + SVM — 44.0792858 (2024-04-03)
CSP + LDA — 39.4492859 (2024-04-03)
DLCSPauto + shLDA — 38.8442857 (2024-04-03)
EEGNet-8,2 — 35.3514286 (2024-04-03)
MDM — 33.4078569 (2024-04-03)
EEGNeX — 30.215714 (2024-04-03)
EEGITNet — 25.7807146 (2024-04-03)
DeepConvNet — 24.1678569 (2024-04-03)
EEGTCNet — 17.9464288 (2024-04-03)
ACM + TS + SVM — 64.3835718 (2024-04-03)
TS + EL — 63.840714199999994 (2024-04-03)
TS + LR — 62.762142 (2024-04-03)
TS + SVM — 61.469286499999995 (2024-04-03)
FgMDM — 56.9400009 (2024-04-03)
ShallowConvNet — 48.9364276 (2024-04-03)
FBCSP + SVM — 45.212857299999996 (2024-04-03)
CSP + SVM — 44.0792858 (2024-04-03)
CSP + LDA — 39.4492859 (2024-04-03)
DLCSPauto + shLDA — 38.8442857 (2024-04-03)
EEGNet-8,2 — 35.3514286 (2024-04-03)
MDM — 33.4078569 (2024-04-03)
EEGNeX — 30.215714 (2024-04-03)
EEGITNet — 25.7807146 (2024-04-03)
DeepConvNet — 24.1678569 (2024-04-03)
EEGTCNet — 17.9464288 (2024-04-03)
ACM + TS + SVM — 64.3835718 (2024-04-03)
TS + EL — 63.840714199999994 (2024-04-03)
TS + LR — 62.762142 (2024-04-03)
TS + SVM — 61.469286499999995 (2024-04-03)
FgMDM — 56.9400009 (2024-04-03)
ShallowConvNet — 48.9364276 (2024-04-03)
FBCSP + SVM — 45.212857299999996 (2024-04-03)
CSP + SVM — 44.0792858 (2024-04-03)
CSP + LDA — 39.4492859 (2024-04-03)
DLCSPauto + shLDA — 38.8442857 (2024-04-03)
EEGNet-8,2 — 35.3514286 (2024-04-03)
MDM — 33.4078569 (2024-04-03)
EEGNeX — 30.215714 (2024-04-03)
EEGITNet — 25.7807146 (2024-04-03)
DeepConvNet — 24.1678569 (2024-04-03)
EEGTCNet — 17.9464288 (2024-04-03)
ACM + TS + SVM — 64.3835718 (2024-04-03)
2024-04-03 — ACM + TS + SVM: Accuracy 64.3835718
Rank
Model
Accuracy
training time (s)
CO2 Emission (g)
Paper
Code
Year
1
ACM + TS + SVM
64.3835718
335.21023
6.1498658200000005
The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark
NeuroTechX/moabb
2024
2
TS + EL
63.840714199999994
34.0226515
0.0319534623
The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark
NeuroTechX/moabb
2024
3
TS + LR
62.762142
2.12094548
0.00205973584
The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark
NeuroTechX/moabb
2024
4
TS + SVM
61.469286499999995
15.092744999999999
0.014714955200000001
The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark
NeuroTechX/moabb
2024
5
FgMDM
56.9400009
3.4260148399999997
0.00332279971
The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark
NeuroTechX/moabb
2024
6
ShallowConvNet
48.9364276
100.2113981
22.743277258
The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark
NeuroTechX/moabb
2024
7
FBCSP + SVM
45.212857299999996
37.9020129
0.030076381000000003
The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark
NeuroTechX/moabb
2024
8
CSP + SVM
44.0792858
677.4126650000001
0.5357583659999999
The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark
NeuroTechX/moabb
2024
9
CSP + LDA
39.4492859
4.84518394
0.0037056161800000003
The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark
NeuroTechX/moabb
2024
10
DLCSPauto + shLDA
38.8442857
4.82886682
0.00369364373
The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark
NeuroTechX/moabb
2024
11
EEGNet-8,2
35.3514286
34.2388724
10.5262206565
The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark
NeuroTechX/moabb
2024
12
MDM
33.4078569
2.01196917
0.00188059405
The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark
NeuroTechX/moabb
2024
13
EEGNeX
30.215714
126.255782
35.190156514
The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark
NeuroTechX/moabb
2024
14
EEGITNet
25.7807146
43.4866037
13.394392257000002
The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark
NeuroTechX/moabb
2024
15
DeepConvNet
24.1678569
73.0829022
30.440530905000003
The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark
NeuroTechX/moabb
2024
16
EEGTCNet
17.9464288
47.42458
15.281205185
The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark
NeuroTechX/moabb
2024
17
ACM + TS + SVM
64.3835718
335.21023
6.1498658200000005
The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark
NeuroTechX/moabb
2024
18
TS + EL
63.840714199999994
34.0226515
0.0319534623
The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark
NeuroTechX/moabb
2024
19
TS + LR
62.762142
2.12094548
0.00205973584
The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark
NeuroTechX/moabb
2024
20
TS + SVM
61.469286499999995
15.092744999999999
0.014714955200000001
The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark
NeuroTechX/moabb
2024
1–20 / 64
다음 →
페이지당
10
20
50
100