Scene Classification on AID TR=20%
97.49AccuracySelectiveMAE
Evaluation Results
| Method | Links | |
|---|---|---|
| SelectiveMAEBackbone=ViT-L [2], Params (M)=307, Throughput/Minute=533k2024.06 | 97.49 | |
| ViT-BPretrain=MAE, Backbone=ViT-B, Method=—2022.08 | 97.47 | |
| SelectiveMAEBackbone=ViT-L [2], Params (M)=307, Throughput/Minute=533k, Pre-training=OpticalRS-13 (4M)2024.06 | 97.25 | |
| ViTAE-BPretrain=MAE, Backbone=ViTAE-B, Method=—2022.08 | 97.2 | |
| SelectiveMAEBackbone=ViT-B [2], Params (M)=86, Throughput/Minute=556k2024.06 | 97.1 | |
| LSKNet-S#P=14.4M, FLOPS=54.4G2024.03 | 97.05 | |
| RVSABackbone=VIT-B+RVSA [21], Params (M)=862024.06 | 97.03 | |
| ViTAE-B + RVSAPretrain=MAE, Backbone=ViTAE-B + RVSA, Method=—2022.08 | 97.03 | |
| RVSA#P=114.4M, FLOPS=301.3G2024.03 | 97.01 | |
| ViTAE-B + RVSA♦Pretrain=MAE, Backbone=ViTAE-B + RVSA*, Method=—2022.08 | 97.01 | |
| ViT-B + RVSAPretrain=MAE, Backbone=ViT-B + RVSA, Method=—2022.08 | 96.92 | |
| RSP-VITAE#P=19.3M, FLOPS=119.1G2024.03 | 96.91 | |
| VITAEv2-SPretrain=RSP, Backbone=VITAEv2-S, Method=—2022.08 | 96.91 | |
| RingMoBackbone=Swin-B [102], Params (M)=882024.06 | 96.9 | |
| SelectiveMAEBackbone=ViT-B [2], Params (M)=86, Throughput/Minute=556k, Pre-training=OpticalRS-13 (4M)2024.06 | 96.9 | |
| RingMoPretrain=RingMo [32], Backbone=Swin-B, Method=—2022.08 | 96.9 | |
| ViTAE-B + VSAPretrain=MAE, Backbone=ViTAE-B + VSA, Method=—2022.08 | 96.9 | |
| ViT-B + RVSA♦Pretrain=MAE, Backbone=ViT-B + RVSA*, Method=—2022.08 | 96.86 | |
| ViT-B + VSAPretrain=MAE, Backbone=ViT-B + VSA, Method=—2022.08 | 96.85 | |
| RSP-Swin#P=27.5M, FLOPS=37.7G2024.03 | 96.83 | |
| RSP-R50#P=25.6M, FLOPS=86.3G2024.03 | 96.81 | |
| LSKNet-T#P=4.3M, FLOPS=19.2G2024.03 | 96.8 | |
| CSPTPretrain=CSPT [80], Backbone=ViT-B, Method=—2022.08 | 96.75 | |
| OREOLEBackbone=VIT-G [43], Params (M)=9142024.06 | 96.71 | |
| VITAEv2-SPretrain=IMP, Backbone=VITAEv2-S, Method=—2022.08 | 96.61 | |
| MAEBackbone=ViT-B [2], Params (M)=86, Throughput/Minute=264k, Pre-training=OpticalRS-13 (4M)2024.06 | 96.58 | |
| Swin-TPretrain=IMP, Backbone=Swin-T, Method=—2022.08 | 96.55 | |
| RingMoPretrain=RingMo [32], Backbone=ViT-B, Method=—2022.08 | 96.54 | |
| FENet#P=23.9M, FLOPS=92.0G2024.03 | 96.45 | |
| MGML-FENetPretrain=IMP, Backbone=DenseNet-121, Method=MGML-FENet [77]2022.08 | 96.45 | |
| ScaleMAEBackbone=ViT-L [2], Params (M)=307, Throughput/Minute=206k2024.06 | 96.44 | |
| CSPTPretrain=CSPT [80], Backbone=ViT-L, Method=—2022.08 | 96.3 | |
| UPetu#P=87.7M, FLOPS=>322.2G2024.03 | 96.29 | |
| CTNet2024.03 | 96.25 | |
| F2BRBM#P=25.6M, FLOPS=86.3G2024.03 | 96.05 | |
| F2BRBMPretrain=IMP, Backbone=ResNet-50, Method=F2BRBM [5]2022.08 | 96.05 | |
| MBENet#P=23.9M, FLOPS=108.5G2024.03 | 96 | |
| AGOSType=CNN, Backbone=DenseNet-1212022.05 | 95.81 | |
| CADNetType=CNN, Year=20202022.05 | 95.73 | |
| MBLANet2024.03 | 95.6 | |
| MBLANetType=CNN, Year=20212022.05 | 95.6 | |
| FSCNet#P=28.8M, FLOPS=166.1G2024.03 | 95.56 | |
| AGOSType=CNN, Backbone=ResNet-1012022.05 | 95.54 | |
| KFBNet2024.03 | 95.5 | |
| GFMBackbone=Swin-B [102], Params (M)=882024.06 | 95.47 | |
| GRMANet#P=54.1M, FLOPS=171.4G2024.03 | 95.43 | |
| ConvNext#P=28.0M, FLOPS=93.7G2024.03 | 95.43 | |
| GRMANetPretrain=IMP, Backbone=ResNet-50, Method=GRMANet [73]2022.08 | 95.43 | |
| ASPPretrain=ASP [76], Backbone=ResNet-101, Method=—2022.08 | 95.4 | |
| TOVBackbone=ResNet-50 [101], Params (M)=262024.06 | 95.16 | |
| SatMAEBackbone=ViT-L [2], Params (M)=307, Throughput/Minute=205k2024.06 | 95.02 | |
| AGOSType=CNN, Backbone=ResNet-502022.05 | 94.99 | |
| SatLasBackbone=Swin-B [102], Params (M)=88, Throughput/Minute=243k2024.06 | 94.96 | |
| IDCCP#P=25.6M, FLOPS=86.3G2024.03 | 94.8 | |
| LSENet#P=25.9M, FLOPS=>86.3G2024.03 | 94.41 | |
| LSENetPretrain=IMP, Backbone=VGG-16, Method=LSENet [42]2022.08 | 94.41 | |
| EAM#P=>42.3M, FLOPS=>164.32024.03 | 94.26 | |
| EAMPretrain=IMP, Backbone=ResNet-101, Method=EAM [74]2022.08 | 94.26 | |
| LiGNetType=CNN, Year=20212022.05 | 94.17 | |
| LSENetType=CNN, Year=20212022.05 | 94.07 | |
| DSENetType=CNN, Year=20212022.05 | 94.02 | |
| DMSMILType=CNN, Year=20212022.05 | 93.98 | |
| MF2NetType=CNN, Year=20202022.05 | 93.82 | |
| ViT-B#P=86.0M, FLOPS=118.9G2024.03 | 93.81 | |
| ViT-BPretrain=IMP, Backbone=ViT-B, Method=—2022.08 | 93.81 | |
| GASSLBackbone=ResNet-50 [101], Params (M)=262024.06 | 93.55 | |
| MSANet#P=>42.3M, FLOPS=>164.32024.03 | 93.53 | |
| MSANetPretrain=IMP, Backbone=ResNet-101, Method=MSANet [75]2022.08 | 93.53 | |
| SeCoBackbone=ResNet-50 [101], Params (M)=262024.06 | 93.47 | |
| MSDFFType=CNN, Year=20202022.05 | 93.47 | |
| MG-CAP#P=>42.3M, FLOPS=>164.3G2024.03 | 93.34 | |
| MG-CAPType=CNN, Year=20202022.05 | 93.34 | |
| SCCov#P=13.0M2024.03 | 93.12 | |
| GBNetType=CNN, Year=20202022.05 | 92.2 | |
| MS2APType=CNN, Year=20212022.05 | 92.19 | |
| MSCPType=CNN, Year=20182022.05 | 91.52 | |
| SSL4EOBackbone=ViT-S [2], Params (M)=222024.06 | 91.06 | |
| RBFFPretrain=IMP, Backbone=MobileNet-V2 [78], Method=RBFF [79]2022.08 | 91.02 | |
| CACOBackbone=ResNet-50 [101], Params (M)=262024.06 | 90.88 | |
| ARCNetType=RNN, Year=20182022.05 | 88.75 | |
| APNetType=CNN, Year=20192022.05 | 88.56 | |
| MIDCNetType=CNN, Year=20202022.05 | 88.26 | |
| RANetType=CNN, Year=20202022.05 | 88.12 | |
| SPPNetType=CNN, Year=2017, Note=Conducted by authors2022.05 | 87.44 | |
| TEXNetType=CNN, Year=20172022.05 | 87.32 | |
| AlexNetType=CNN, Year=20172022.05 | 86.86 | |
| VGGNet-16Type=CNN, Year=20172022.05 | 86.59 | |
| GoogLeNetType=CNN, Year=20172022.05 | 83.44 | |
| AGANType=GAN, Year=20192022.05 | 78.95 | |
| MARTAType=GAN, Year=20172022.05 | 75.39 | |
| BOVW(SIFT)Type=Hand-crafted, Year=20172022.05 | 62.49 | |
| PLSA(SIFT)Type=Hand-crafted, Year=20172022.05 | 56.24 | |
| LDA(SIFT)Type=Hand-crafted, Year=20172022.05 | 51.73 |