| language: | |
| - en | |
| license: mit | |
| library_name: keras | |
| tags: | |
| - remote-sensing | |
| - multispectral | |
| - hyperspectral | |
| - uncertainty-quantification | |
| - conformal-prediction | |
| metrics: | |
| - accuracy | |
| - kappa | |
| - coverage | |
| # 6-Band Hyperspectral Classification Model Registry | |
| This repository hosts deep neural network checkpoints trained on the 6-band hyperspectral benchmark dataset (330x307x6, 7 classes) for conformal uncertainty quantification and high-precision remote sensing classification. | |
| ## Benchmark Architectures | |
| - **AlexNet CNN Backbone**: 6-channel convolutional feature extractor | |
| - **GFNet (Global Filter Network)**: Frequency-domain 2D FFT global spatial interaction network | |
| - **ViT_UNet**: Hybrid Vision Transformer and U-Net encoder-decoder architecture | |
| ## Checkpoints Included | |
| - `baseline/models/AlexNet_CNN_best.keras` | |
| - `baseline/models/GFNet_best.keras` | |
| - `baseline/models/ViT_UNet_best.keras` | |
| - `baseline/models/AlexNet_CNN_final.keras` | |
| - `baseline/models/GFNet_final.keras` | |
| - `baseline/models/ViT_UNet_final.keras` | |
| ## Authors & Attribution | |
| - **Principal Author**: Danesh Selwal (`selwaldanesh@gmail.com`) | |
| - **Co-authored by**: Claude (`claude@anthropic.com`) | |