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ResearchFormerly WizWand

Multi-label structural damage classification on xROAD 20-class setting 1.0 (test)

42.77AccuracySCAFFOLD
38.287639.451340.61541.7787Jun 2, 2026
Updated 5mo ago

Evaluation results

MethodLinks
SCAFFOLDNumber of Clusters (M)=1 (no clustering), Backbone=ResNet-182026.0642.7764.1145.7553.4
MOONNumber of Clusters (M)=3, Backbone=ResNet-182026.0642.364.6350.3656.61
LocalNumber of Clusters (M)=/, Backbone=ResNet-182026.0641.4445.0160.7951.72
Clustered-DRAPRNumber of Clusters (M)=2, Backbone=ResNet-182026.0640.7467.551.9258.69
IFCANumber of Clusters (M)=2, Backbone=ResNet-182026.0640.765.574956.09
FedProxNumber of Clusters (M)=3, Backbone=ResNet-182026.0640.6965.2249.2956.15
Clustered-DRAPRNumber of Clusters (M)=3, Backbone=ResNet-182026.0640.6668.1152.1359.06
FedProxNumber of Clusters (M)=2, Backbone=ResNet-182026.0640.5365.3949.2656.19
IFCANumber of Clusters (M)=3, Backbone=ResNet-182026.0640.5265.4749.1756.16
MOONNumber of Clusters (M)=2, Backbone=ResNet-182026.0640.3765.5147.6855.19
Clustered-DRAPRNumber of Clusters (M)=1 (no clustering), Backbone=ResNet-182026.0640.365.7548.2355.64
MOONNumber of Clusters (M)=1 (no clustering), Backbone=ResNet-182026.0640.2564.7947.5654.85
FedProxNumber of Clusters (M)=1 (no clustering), Backbone=ResNet-182026.0639.9865.947.9455.5
FedAvgNumber of Clusters (M)=3, Backbone=ResNet-182026.0639.4964.6347.4254.7
SCAFFOLDNumber of Clusters (M)=2, Backbone=ResNet-182026.0639.4365.5746.1954.2
FedAvgNumber of Clusters (M)=2, Backbone=ResNet-182026.0639.2465.7845.8254.01
FedAvgNumber of Clusters (M)=1 (no clustering), Backbone=ResNet-182026.0638.7166.0644.6553.28
SCAFFOLDNumber of Clusters (M)=3, Backbone=ResNet-182026.0638.4665.1945.6453.69