整个操作在Transformer编码器的块中执行,其中每个Transformer块由光谱和空间形态特征提取块和残差多头交叉注意块组成。 Spectral Morph和Spatial Morph两层的输出以通道形式(X′patch)与Xcls级联,以生成整个形态块的最终输出。来自光谱和空间形态块的输出通道是输入Xpatch的一半,因此,在将两者concatenate之后,通道的数量变得...
Method 1.Spectral–Spatial Feature Extraction:将经过PCA降维后的特征图{(m×n×l)->(m×n×b)}经过一个3-D卷积层和一个2-D卷积层进行初初始特征编码。 2.Gaussian-W eighted Feature T okenizer:通过两层卷积运算提取的特征携带光谱和空间信息,但不能充分描述地面物体的特征。因此,特征图被进一步定义为语...
The proposed spectral-spatial multi-layer perceptron network exclusively utilizes multi-layer perceptron to represent and classify hyperspectral images. Specifically, the spectral multi-layer perceptron is investigated to model the long-range dependencies along the spectral dimension, because all diagnostic ...
只有经过这两个步骤,才能得到基于学习稀疏字典的分类结果。 Yue, J.; Zhao, W.; Mao, S.; Liu, H. Spectral-spatial classification of hyperspectral images using deep convolutional neural networks. Remote Sens. Lett. 2015, 6, 468–477. Makantasis, K.; Karantzalos, K.; Doulamis, A.; Doulamis...
SpectralSpatial Classification of Hyperspectral Imagery with 3D Convolutional Neural Network 基于3DCNN的高光谱图像分类 特征分析 实验设置 实验结果和分析 paviaU 最近的研究表明,用空谱信息可以显著提升高光谱图像分类的性能。高光谱图像数据是典型的3D立方体格式。因此三维空间滤波器提供了一种简单有效的方法来同时...
Experimental results demonstrate that the proposed spectral–spatial hyperspectral image classification method can show competitive performance. Multi-feature learning based on deep learning exhibits a great potential on the classification of hyperspectral images. When the number of samples is 30 % and the...
spectral-spatialpulses 青云英语翻译 请在下面的文本框内输入文字,然后点击开始翻译按钮进行翻译,如果您看不到结果,请重新翻译! 翻译结果1翻译结果2翻译结果3翻译结果4翻译结果5 翻译结果1复制译文编辑译文朗读译文返回顶部 光谱spatialpulses 翻译结果2复制译文编辑译文朗读译文返回顶部...
spectralspatial卷积hsiclassihyperspectral remotesensing Article Spectral–SpatialClassificationofHyperspectral Imagerywith3DConvolutionalNeuralNetwork YingLi 1, *,HaokuiZhang 1 andQiangShen 2 1 SchoolofComputerScience,NorthwesternPolytechnicalUniversity,Xi’an710129,Shaanxi,China; hkzhang1991@mail.nwpu.edu 2 Dep...
使用hypergraph可以尽可能的描述样本点与整个样本数据的属性关系,只能当属性(超边)重叠多的时候才可以说明两个样本是属于通一类,它避免了只比较两个数据样本相似性的缺陷。 SWBH用于提取HSI的光谱特征。它使属于不同类的像素之间的距离最大化,并使具有相同类的像素保持接近。
In this letter, a novel deep learning framework for hyperspectral image classification using both spectral and spatial features is presented. The framework is a hybrid of principal component analysis, deep convolutional neural networks (DCNNs) and logistic regression (LR). The DCNNs for hierarchically...