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SOTA
Scene Recognition
Scene Recognition On Aid
Scene Recognition On Aid
Metrics
Accuracy
Results
Performance results of various models on this benchmark
Columns
Model Name
Accuracy
Paper Title
AGOS
97.43
All Grains, One Scheme (AGOS): Learning Multi-grain Instance Representation for Aerial Scene Classification
LSENet
96.36
Local semantic enhanced convnet for aerial scene recognition
MIDC-Net
92.95
A multiple-instance densely-connected ConvNet for aerial scene classification
0 of 3 row(s) selected.
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Next
HyperAI
HyperAI
Home
Console
Docs
News
Papers
Tutorials
Datasets
Wiki
SOTA
LLM Models
GPU Leaderboard
Events
Search
About
Terms of Service
Privacy Policy
English
HyperAI
HyperAI
Toggle Sidebar
Search the site…
⌘
K
Command Palette
Search for a command to run...
Console
Home
SOTA
Scene Recognition
Scene Recognition On Aid
Scene Recognition On Aid
Metrics
Accuracy
Results
Performance results of various models on this benchmark
Columns
Model Name
Accuracy
Paper Title
AGOS
97.43
All Grains, One Scheme (AGOS): Learning Multi-grain Instance Representation for Aerial Scene Classification
LSENet
96.36
Local semantic enhanced convnet for aerial scene recognition
MIDC-Net
92.95
A multiple-instance densely-connected ConvNet for aerial scene classification
0 of 3 row(s) selected.
Previous
Next
Scene Recognition On Aid | SOTA | HyperAI