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ResearchFormerly WizWand

Cell Classification on Cell classification dataset (test)

89.1F1 ScoreSwin Transformer Base
80.150882.4741584.797587.12085Jul 13, 2022
Updated 8mo ago

Evaluation results

MethodLinks
Swin Transformer BasePre-training=ImageNet, Patch Size=4, Window Size=122022.0789.1
nfnet-f3Pre-training=ImageNet2022.0788.98
nfnet-f4Pre-training=ImageNet2022.0788.48
Swin Transformer largePre-training=ImageNet, Patch Size=4, Window Size=122022.0788.39
Resnet-101Pre-training=ImageNet2022.0787.1
nfnet-f2Pre-training=ImageNet2022.0786.52
Resnet-18Pre-training=ImageNet2022.0786.35
Vit-Base/32Pre-training=ImageNet, Patch Size=322022.0785.07
Resnet-50Pre-training=ImageNet2022.0784.99
ConvNext-smallPre-training=ImageNet2022.0784.795
Efficient-net B5Pre-training=ImageNet2022.0784.63
ConvNext-largePre-training=ImageNet2022.0784.52
Vit-large/32Pre-training=ImageNet, Patch Size=322022.0784.5
Vit-Base/16Pre-training=ImageNet, Patch Size=162022.0784.26
Efficient-net B4Pre-training=ImageNet2022.0784.18
nfnet-f6Pre-training=ImageNet2022.0783.78
Efficient-net B0Pre-training=ImageNet2022.0783.72
Efficient-net B3Pre-training=ImageNet2022.0783.69
Efficient-net B1Pre-training=ImageNet2022.0783.46
nfnet-f1Pre-training=ImageNet2022.0783.4
Efficient-net B2Pre-training=ImageNet2022.0782.8
Resnet-34Pre-training=ImageNet2022.0782.765
Efficient-net B6Pre-training=ImageNet2022.0782.63
nfnet-f0Pre-training=ImageNet2022.0782.035
nfnet-f5Pre-training=ImageNet2022.0781.61
ConvNext-tinyPre-training=ImageNet2022.0781.355
Efficient-net B7Pre-training=ImageNet2022.0781.29
ConvNext-basePre-training=ImageNet2022.0780.675
Vit-large/16Pre-training=ImageNet, Patch Size=162022.0780.495