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Scene Classification on UCM 1.0 (50% train ratio)

99.81Accuracy

ViT-B

Updated 4d ago

Evaluation Results

Method	Links
ViT-B 2022.08		99.81
ViT-B + RVSA 2022.08		99.7
VITAEv2-S 2022.08		99.62
ViTAE-B 2022.08		99.6
ViT-B + RVSA♦ 2022.08		99.58
ViTAE-B + RVSA 2022.08		99.56
ViTAE-B + RVSA♦ 2022.08		99.5
Swin-T 2022.08		99.43
VITAEv2-S 2022.08		99.43
ViTAE-B + VSA 2022.08		99.43
ViT-B + VSA 2022.08		99.41
AGOS 2022.05		99.34
AGOS 2022.05		99.29
GRMANet 2022.08		99.29
AGOS 2022.05		99.24
ViT-B 2022.08		99.15
DMSMIL 2022.05		99.09
MSDFF 2022.05		98.85
EAM 2022.08		98.81
F2BRBM 2022.08		98.64
CADNet 2022.05		98.57
LSENet 2022.08		98.53
MS2AP 2022.05		98.38
LSENet 2022.05		97.94
MSANet 2022.08		97.8
GBNet 2022.05		97.05
ARCNet 2022.05		96.81
DSENet 2022.05		96.19
RBFF 2022.08		95.83
APNet 2022.05		95.01
MIDCNet 2022.05		94.93
RANet 2022.05		94.79
SPPNet 2022.05		94.77
TEXNet 2022.05		94.22
VGGNet-16 2022.05		94.14
AlexNet 2022.05		93.98
GoogLeNet 2022.05		92.7
AGAN 2022.05		89.06
PARTLETS 2022.05		88.76
MARTA 2022.05		85.5
BOVW(SIFT) 2022.05		73.48
PLSA(SIFT) 2022.05		67.55
LDA(SIFT) 2022.05		59.24