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)