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, N. Deep supervised learning for hyperspectral data cla...
Spectral-spatial classification of hyperspectral images has been the subject of many studies in recent years. When there are only a few labeled pixels for training and a skewed class label distribution, this task becomes very challenging because of the increased risk of overfitting when training a ...
Bag of Tricks for Image Classification with Convolutional Neural Networks CVPR2019 CNN Tricks Bag of Tricks for Image Classification with Convolutional Neural Networks 原文链接:https://arxiv.org/abs/1812.01187 如题目所述,本篇文章总结了一些CNN的技巧。包括预处理、损失函数、batchsize、网络结构、标签...
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...
论文翻译:Deep Convolutional Capsule Network for Hyperspectral Image Spectral and Spectral-Spatial Classification 基于深度卷积胶囊网络的高光谱图像和光谱-空间分类 摘要 最近在监督分类问题中展现出优势的胶囊网络被认为将是深度学习的下一个时代。胶囊网络利用向量代替标量来表示特征,从而增加了特征的表现能力。本...
spectral-spatial classificationHyperspectral imaging (HSI) is an emerging imaging modality that can provide a noninvasive tool for cancer detection and image-... Ling,Guolan,Dongsheng,... - Proceedings of SPIE--the International Society for Optical Engineering 被引量: 2发表: 2017年 Deep learning ...
《Spectral–Spatial Morphological Attention Transformer for Hyperspectral Image Classification》论文笔记 论文作者:Swalpa Kumar Roy, Ankur Deria, Chiranjibi Shah, et al. 论文发表年份:2023 模型简称:morphFormer 发表期刊:IEEE Transactions on Geoscience and Remote Sensing...
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。
Hyperspectral remote sensing has a strong ability in information expression, so it provides better support for classification. The methods proposed to deal the hyperspectral data classification problems were build one by one. However, most of them committed to spectral feature extraction that means wasti...
《Spectral–Spatial Feature Tokenization Transformer for Hyperspectral Image Classification》论文笔记 论文作者:Le Sun, Guangrui Zhao, Y uhui Zheng, et al. 论文发表年份:2022 模型简称:SSFTT 发表期刊:IEEE Transactions on Geoscience and Remote Sensing...