Scene Classification on UC Merced Land Use Dataset

Metric: Accuracy (%) (higher is better)

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#	Model↕	Accuracy (%)▼	Extra Data	Paper	Date↕	Code
1	µ2Net+ (ViT-L/16)	100	No	A Continual Development Methodology for Large-sc...	2022-09-15	Code
2	AGOS	99.88	No	All Grains, One Scheme (AGOS): Learning Multi-gr...	2022-05-06	Code
3	LSE-Net	99.78	No	-	-	Code
4	ResNet50	99.61	No	In-domain representation learning for remote sen...	2019-11-15	Code
5	MSMatch	98.33	No	MSMatch: Semi-Supervised Multispectral Scene Cla...	2021-03-18	Code
6	MIDC-Net	97.4	No	-	-	Code

#1µ2Net+ (ViT-L/16)SOTA
100
Accuracy (%)· 2022-09-15
A Continual Development Methodology for Large-scale Multitask Dynamic ML Systems Code
#2AGOSSOTA
99.88
Accuracy (%)· 2022-05-06
All Grains, One Scheme (AGOS): Learning Multi-grain Instance Representation for Aerial Scene Classification Code
#3LSE-Net
99.78
Accuracy (%)
No paperCode
#4ResNet50SOTA
99.61
Accuracy (%)· 2019-11-15
In-domain representation learning for remote sensing Code
#5MSMatch
98.33
Accuracy (%)· 2021-03-18
MSMatch: Semi-Supervised Multispectral Scene Classification with Few Labels Code
#6MIDC-Net
97.4
Accuracy (%)
No paperCode