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ResearchFormerly WizWand

Gesture Recognition on GrabMyo (cross-subject)

54.31AccuracySASG-DA
43.930846.625449.3252.0146Nov 11, 2025
Updated 8mo ago

Evaluation results

MethodLinks
SASG-DABackbone=STCNet2025.1154.31
SASG-DABackbone=TDCT2025.1153.53
MinorityBackbone=TDCT2025.1152.65
CADSBackbone=TDCT2025.1152.64
CADSBackbone=STCNet2025.1152.5
MixupBackbone=STCNet2025.1152.05
MinorityBackbone=STCNet2025.1152.01
PatchEMGBackbone=STCNet2025.1151.41
MixupBackbone=TDCT2025.1151
Jittering & ScalingBackbone=STCNet2025.1150.07
SASG-DABackbone=GengNet2025.1150.06
PatchEMGBackbone=TDCT2025.1150.01
Jittering & ScalingBackbone=TDCT2025.1149.66
UpsampleBackbone=STCNet2025.1149.23
RIMBackbone=STCNet2025.1149.18
BaselineBackbone=STCNet2025.1149.09
UpsampleBackbone=TDCT2025.1148.93
CADSBackbone=GengNet2025.1148.87
FreqMaskBackbone=STCNet2025.1148.79
NTDBackbone=GengNet2025.1148.77
MixupBackbone=GengNet2025.1148.68
NTDBackbone=TDCT2025.1148.67
PatchEMGBackbone=GengNet2025.1148.63
BaselineBackbone=TDCT2025.1148.5
RIMBackbone=TDCT2025.1148.48
FreqMixBackbone=TDCT2025.1148.35
FreqMaskBackbone=TDCT2025.1148.23
MinorityBackbone=GengNet2025.1148.12
NTDBackbone=STCNet2025.1148.05
FreqMixBackbone=STCNet2025.1148.04
DiffMixBackbone=STCNet2025.1147.87
Dominant ShuffleBackbone=TDCT2025.1147.68
Jittering & ScalingBackbone=GengNet2025.1147.54
Dominant ShuffleBackbone=STCNet2025.1147.52
DESAMBackbone=GengNet2025.1147.38
BaselineBackbone=GengNet2025.1147.27
FreqMixBackbone=GengNet2025.1147.1
DiffMixBackbone=TDCT2025.1146.76
RIMBackbone=GengNet2025.1146.59
UpsampleBackbone=GengNet2025.1146.51
FreqMaskBackbone=GengNet2025.1146.26
Dominant ShuffleBackbone=GengNet2025.1145.99
DiffMixBackbone=GengNet2025.1145.77
DESAMBackbone=STCNet2025.1144.66
DESAMBackbone=TDCT2025.1144.33