A Fast Dense Spectral–Spatial Convolution Network Framework for Hyperspectral Images Classification
A Fast Dense Spectral–Spatial Convolution Network Framework for Hyperspectral Images Classification高光谱分类框架阅读 论文链接 代码链接 内容 提出了一种端到端快速密集谱空间卷积（FDSSC）的HSI分类框架。采用不同卷积核大小分别提取光谱和空间特征，采用有效卷积方法降低高维。密不可分的连接结构每个
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相关文章
- 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. 【论文笔记】Spectral-Spatial Attention Network for Hyperspectral Image Classification
- 4. 【论文翻译】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. 论文总结Classification of Hyperspectral Images Based on Multiclass Spatial–Spectral GAN
- 7. Spectral–Spatial Classification of Hyperspectral Imagery with 3D Convolutional Neural Network
- 8. 【论文浅读】《Deep Pyramidal Residual Networks for Spectral–Spatial Hyperspectral Image Classification》
- 9. Hyperspectral Image Classification in the Presence of Noisy Labels
- 10. 【论文笔记】Spectral-Spatial Exploration for HSIC via the Fusion of FCN