- dataset.py: Create training, validation and test samples in pytorch format.
- models.py:Create models, including ResNet101, ResNet152, Wide ResNet50, Wide ResNet101.
- train.py: Training of GSCNN.
- train_models.py: Train of GSCNNs based on four ResNets.
- evaluation.py: Evaluation of model performance.
- plot.py: Plotting of learning curve.
- predict.py: Prediction for BSV images in China.
- utils.py: Some utilities, including configuration and data augmentation pipelines.
-
Notifications
You must be signed in to change notification settings - Fork 0
ChanceQZ/NoiseBarrierIdentification
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Folders and files
| Name | Name | Last commit message | Last commit date | |
|---|---|---|---|---|
Repository files navigation
About
Code for generation of noise barrier dataset
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published