A Fast Dense Spectral–Spatial Convolution Network Framework for Hyperspectral Images Classification
A Fast Dense Spectral–Spatial Convolution Network Framework for Hyperspectral Images Classification高光譜分類框架閱讀 論文鏈接 代碼鏈接 內容 提出了一種端到端快速密集譜空間卷積（FDSSC）的HSI分類框架。採用不同卷積核大小分別提取光譜和空間特徵，採用有效卷積方法降低高維。密不可分的連接結構每個
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相關文章
- 1. Paper Reading -- 《Spectral-Spatial Attention Networks for Hyperspectral Image Classification》
- 2. A new deep convolutional neural network for fast hyperspectral image classification Review
- 3. 【論文筆記】Spectral-Spatial Attention Network for Hyperspectral Image Classification
- 4. 【論文翻譯】Spectral-Spatial Residual Network for Hyperspectral Image Classification A 3-D Deep Learning F
- 5. Hyperspectral Images Classification Based on Dense Convolutional Networks with Spectral-Wise Attenti
- 6. 論文總結Classification of Hyperspectral Images Based on Multiclass Spatial–Spectral GAN
- 7. Spectral–Spatial Classification of Hyperspectral Imagery with 3D Convolutional Neural Network
- 8. 【論文淺讀】《Deep Pyramidal Residual Networks for Spectral–Spatial Hyperspectral Image Classification》
- 9. Hyperspectral Image Classification in the Presence of Noisy Labels
- 10. 【論文筆記】Spectral-Spatial Exploration for HSIC via the Fusion of FCN