Image Classification on GasHisSDB

Metric: Accuracy (higher is better)

LeaderboardDataset

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#	Model↕	Accuracy▼	Extra Data	Paper	Date↕	Code
1	CoAtNet-1	98.74	No	CoAtNet: Marrying Convolution and Attention for ...	2021-06-09	Code
2	Res2Net-50	98.68	No	Res2Net: A New Multi-scale Backbone Architecture	2019-04-02	Code
3	ResNeXt-50-32x4d	98.59	No	Aggregated Residual Transformations for Deep Neu...	2016-11-16	Code
4	ResNet-50	98.56	No	Deep Residual Learning for Image Recognition	2015-12-10	Code
5	ResNet-18	98.47	No	Deep Residual Learning for Image Recognition	2015-12-10	Code
6	EfficientNet-b0	98.11	No	EfficientNet: Rethinking Model Scaling for Convo...	2019-05-28	Code
7	RegNetY-3.2GF	97.48	No	RegNet: Self-Regulated Network for Image Classif...	2021-01-03	Code
8	DenseNet-169	96.9	No	Densely Connected Convolutional Networks	2016-08-25	Code

#1CoAtNet-1SOTA
98.74
Accuracy· 2021-06-09
CoAtNet: Marrying Convolution and Attention for All Data Sizes Code
#2Res2Net-50SOTA
98.68
Accuracy· 2019-04-02
Res2Net: A New Multi-scale Backbone Architecture Code
#3ResNeXt-50-32x4dSOTA
98.59
Accuracy· 2016-11-16
Aggregated Residual Transformations for Deep Neural Networks Code
#4ResNet-50SOTA
98.56
Accuracy· 2015-12-10
Deep Residual Learning for Image Recognition Code
#5ResNet-18
98.47
Accuracy· 2015-12-10
Deep Residual Learning for Image Recognition Code
#6EfficientNet-b0
98.11
Accuracy· 2019-05-28
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks Code
#7RegNetY-3.2GF
97.48
Accuracy· 2021-01-03
RegNet: Self-Regulated Network for Image Classification Code
#8DenseNet-169
96.9
Accuracy· 2016-08-25
Densely Connected Convolutional Networks Code