调程序感悟：Group lasso-based band selection for hyperspectral image classification
要想跑通这篇文章的程序，关键的三个点如下： 1、一定记住！一定记住！一定记住！一定要提前装好Visual Studio（PS：之前嫌VS2017太占空间，所以卸载了，结果导致程序搞了一早上），因为跑这个代码的glmnet、libsvm两个工具包需要VS编译环境的支持。 2、按照作者给出的链接我们可以下载好glmnet、libsvm的压缩包，然后将它们解压到MATLAB的工具包路径里面，这里需要你找
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相关文章
- 1. Variable precision rough set based unsupervised band selection technique for hyperspectral image cla
- 2. Hyperspectral Band Selection by Multitask Sparsity Puisuit
- 3. Generative Adversarial Networks for Hyperspectral Image Classification
- 4. IGARSS2017_SSRN 读后感DEEP RESIDUAL NETWORKS FOR HYPERSPECTRAL IMAGE CLASSIFICATION
- 5. Hyperspectral Band Selection via Adaptive Subspace Partition Strategy
- 6. 论文解读：BS-Nets: An End-to-End Framework For Band Selection of Hyperspectral Image
- 7. Paper Reading -- 《Spectral-Spatial Attention Networks for Hyperspectral Image Classification》
- 8. 论文阅读：Scalable One-Pass Self-Representation Learning for Hyperspectral Band Selection
- 9. A new deep convolutional neural network for fast hyperspectral image classification Review
- 10. Deep Learning for Hyperspectral Image Classification:An Overview