Hyperspectral Image Classification on Indian Pines 50/50 (test)
93.7Mean Test AccuracyCP
Evaluation Results
| Method | Links | |
|---|---|---|
| CPModel Type=CP, Backbone=DenseNet121, Rank (R)=2, Number of trainable parameters=27k2026.05 | 93.7 | |
| TuckerModel Type=Tucker, Backbone=DenseNet121, Rank (R)=2, Number of trainable parameters=27k2026.05 | 92.8 | |
| ScratchModel Type=Scratch, Backbone=DenseNet121, Rank (R)=2, Number of trainable parameters=629k2026.05 | 92.2 | |
| ReduceModel Type=Reduce, Backbone=DenseNet121, Rank (R)=2, Number of trainable parameters=27k2026.05 | 86.7 |