Image Classification on TCMP-300

Metric: Accuracy (% ) (higher is better)

LeaderboardDataset

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#	Model↕	Accuracy (% )▼	Extra Data	Paper	Date↕	Code
1	Swin-Base	89.64	No	-	-	-
2	ConNeXt-Tiny	89.43	No	-	-	-
3	Swin-Tiny	89.39	No	-	-	-
4	Swin-Small	89.13	No	-	-	-
5	DenseNet-161	88.78	No	-	-	-
6	RegNet-X	88.57	No	-	-	-
7	ResNet-50	87.47	No	-	-	-
8	ViT-Base-16	87.19	No	-	-	-
9	EfficientNet-B0	86.13	No	-	-	-
10	ShuffleNetV2	83.65	No	-	-	-
11	MobileNetV3-Large	82.99	No	-	-	-

#1Swin-Base
89.64
Accuracy (% )
No paper
#2ConNeXt-Tiny
89.43
Accuracy (% )
No paper
#3Swin-Tiny
89.39
Accuracy (% )
No paper
#4Swin-Small
89.13
Accuracy (% )
No paper
#5DenseNet-161
88.78
Accuracy (% )
No paper
#6RegNet-X
88.57
Accuracy (% )
No paper
#7ResNet-50
87.47
Accuracy (% )
No paper
#8ViT-Base-16
87.19
Accuracy (% )
No paper
#9EfficientNet-B0
86.13
Accuracy (% )
No paper
#10ShuffleNetV2
83.65
Accuracy (% )
No paper
#11MobileNetV3-Large
82.99
Accuracy (% )
No paper