Awesome
PyTorch_UCMerced_LandUse
Dataset
Result
lr = 0.001, batch_size = 8
| Epoch | 4 | 100 | 200 |
|---|---|---|---|
| ResNet18 | 45.48% | 86.19% | 91.90% |
| ResNet34 | 44.05% | 79.52% | 79.52% |
File structure
├── Images
│ ├── agricultural
│ ├── airplane
│ ├── baseballdiamond
│ ├── beach
│ ├── buildings
│ ├── chaparral
│ ├── denseresidential
│ ├── forest
│ ├── freeway
│ ├── golfcourse
│ ├── harbor
│ ├── intersection
│ ├── mediumresidential
│ ├── mobilehomepark
│ ├── overpass
│ ├── parkinglot
│ ├── river
│ ├── runway
│ ├── sparseresidential
│ ├── storagetanks
│ └── tenniscourt
├── README.md
├── checkpoint
│ ├── LeNet
│ │ └── ckpt.pth
│ └── ResNet
│ └── ckpt.pth
├── main.py
├── models
│ ├── __init__.py
│ ├── lenet.py
│ └── resnet.py
└── utils.py
Reference
- Yi Yang and Shawn Newsam, "Bag-Of-Visual-Words and Spatial Extensions for Land-Use Classification," ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM GIS), 2010.