paper-with-me

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)
RankModel Accuracytraining time (s)CO2 Emission (g) PaperCodeYear
1 ACM + TS + SVM 64.3835718335.210236.1498658200000005 The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark NeuroTechX/moabb 2024
2 TS + EL 63.84071419999999434.02265150.0319534623 The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark NeuroTechX/moabb 2024
3 TS + LR 62.7621422.120945480.00205973584 The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark NeuroTechX/moabb 2024
4 TS + SVM 61.46928649999999515.0927449999999990.014714955200000001 The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark NeuroTechX/moabb 2024
5 FgMDM 56.94000093.42601483999999970.00332279971 The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark NeuroTechX/moabb 2024
6 ShallowConvNet 48.9364276100.211398122.743277258 The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark NeuroTechX/moabb 2024
7 FBCSP + SVM 45.21285729999999637.90201290.030076381000000003 The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark NeuroTechX/moabb 2024
8 CSP + SVM 44.0792858677.41266500000010.5357583659999999 The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark NeuroTechX/moabb 2024
9 CSP + LDA 39.44928594.845183940.0037056161800000003 The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark NeuroTechX/moabb 2024
10 DLCSPauto + shLDA 38.84428574.828866820.00369364373 The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark NeuroTechX/moabb 2024
11 EEGNet-8,2 35.351428634.238872410.5262206565 The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark NeuroTechX/moabb 2024
12 MDM 33.40785692.011969170.00188059405 The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark NeuroTechX/moabb 2024
13 EEGNeX 30.215714126.25578235.190156514 The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark NeuroTechX/moabb 2024
14 EEGITNet 25.780714643.486603713.394392257000002 The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark NeuroTechX/moabb 2024
15 DeepConvNet 24.167856973.082902230.440530905000003 The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark NeuroTechX/moabb 2024
16 EEGTCNet 17.946428847.4245815.281205185 The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark NeuroTechX/moabb 2024
17 ACM + TS + SVM 64.3835718335.210236.1498658200000005 The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark NeuroTechX/moabb 2024
18 TS + EL 63.84071419999999434.02265150.0319534623 The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark NeuroTechX/moabb 2024
19 TS + LR 62.7621422.120945480.00205973584 The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark NeuroTechX/moabb 2024
20 TS + SVM 61.46928649999999515.0927449999999990.014714955200000001 The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark NeuroTechX/moabb 2024
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