Scene Classification On Uc Merced Land Use
Metrics
Accuracy (%)
Results
Performance results of various models on this benchmark
Model Name | Accuracy (%) | Paper Title | Repository |
|---|---|---|---|
| LSE-Net | 99.78 | Local semantic enhanced convnet for aerial scene recognition | |
| MIDC-Net | 97.40 | A multiple-instance densely-connected ConvNet for aerial scene classification | |
| MSMatch | 98.33 | MSMatch: Semi-Supervised Multispectral Scene Classification with Few Labels | - |
| AGOS | 99.88 | All Grains, One Scheme (AGOS): Learning Multi-grain Instance Representation for Aerial Scene Classification | - |
| ResNet50 | 99.61 | In-domain representation learning for remote sensing | - |
| µ2Net+ (ViT-L/16) | 100 | A Continual Development Methodology for Large-scale Multitask Dynamic ML Systems | - |
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