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SOTA
Image Classification
Image Classification On Resisc45
Image Classification On Resisc45
Metrics
Top 1 Accuracy
Results
Performance results of various models on this benchmark
Columns
Model Name
Top 1 Accuracy
Paper Title
Repository
LWGANet L1
95.70
LWGANet: A Lightweight Group Attention Backbone for Remote Sensing Visual Tasks
-
ResNet50 (ImageNet-supervised)
88.56
Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision
-
BYOL (ResNet200-w2)
92.53
-
-
DecoupleNet D2
95.87
DecoupleNet: A Lightweight Backbone Network With Efficient Feature Decoupling for Remote Sensing Visual Tasks
LSENet
93.49
Local semantic enhanced convnet for aerial scene recognition
MIDC-Net
87.99
A multiple-instance densely-connected ConvNet for aerial scene classification
LWGANet L0
95.49
LWGANet: A Lightweight Group Attention Backbone for Remote Sensing Visual Tasks
-
DeiT-B/16
92.48
Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision
-
SimCLR-v2 (ResNet152-w3 + SK)
89.77
Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision
-
SAG-ViT
-
SAG-ViT: A Scale-Aware, High-Fidelity Patching Approach with Graph Attention for Vision Transformers
-
MoCo-v3 (ViT-B/16)
93.35
Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision
-
SwAV (ResNet50-w5)
94.73
Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision
-
ResNet50
96.83
In-domain representation learning for remote sensing
-
MoCo-v2 (ResNet50)
85.4
Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision
-
SEER (RegNet10B)
95.61
Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision
-
CLIP (ViT-B/16)
92.7
Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision
-
DINO (DeiT-B/16)
93.97
Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision
-
AGOS
94.91
All Grains, One Scheme (AGOS): Learning Multi-grain Instance Representation for Aerial Scene Classification
-
LWGANet L2
96.17
LWGANet: A Lightweight Group Attention Backbone for Remote Sensing Visual Tasks
-
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Image Classification On Resisc45 | SOTA | HyperAI