Deep learning for classification of hyperspectral data: A comparative review
In recent years, deep-learning techniques revolutionized the way remote sensing data are
processed. The classification of hyperspectral data is no exception to the rule, but it has …
processed. The classification of hyperspectral data is no exception to the rule, but it has …
Recent advances on spectral–spatial hyperspectral image classification: An overview and new guidelines
Imaging spectroscopy, also known as hyperspectral imaging, has been transformed in the
last four decades from being a sparse research tool into a commodity product available to a …
last four decades from being a sparse research tool into a commodity product available to a …
Multi-scale receptive fields: Graph attention neural network for hyperspectral image classification
Y Ding, Z Zhang, X Zhao, D Hong, W Cai… - Expert Systems with …, 2023 - Elsevier
Hyperspectral image (HSI) classification has attracted wide attention in many fields.
Applying Graph Neural Network (GNN) to HSI classification is one of the research frontiers …
Applying Graph Neural Network (GNN) to HSI classification is one of the research frontiers …
[PDF][PDF] 高光谱遥感影像分类研究进展
杜培军， 夏俊士， 薛朝辉， 谭琨， 苏红军， 鲍蕊 - 遥感学报, 2021 - ygxb.ac.cn
随着模式识别, 机器学习, 遥感技术等相关学科领域的发展, 高光谱遥感影像分类研究取得快速
进展. 本文系统总结和评述了当前高光谱遥感影像分类的相关研究进展, 在总结分类策略的基础 …
进展. 本文系统总结和评述了当前高光谱遥感影像分类的相关研究进展, 在总结分类策略的基础 …
CNN-enhanced graph convolutional network with pixel-and superpixel-level feature fusion for hyperspectral image classification
Recently, the graph convolutional network (GCN) has drawn increasing attention in the
hyperspectral image (HSI) classification. Compared with the convolutional neural network …
hyperspectral image (HSI) classification. Compared with the convolutional neural network …
Automatic COVID-19 lung infected region segmentation and measurement using CT-scans images
History shows that the infectious disease (COVID-19) can stun the world quickly, causing
massive losses to health, resulting in a profound impact on the lives of billions of people …
massive losses to health, resulting in a profound impact on the lives of billions of people …
An overview on spectral and spatial information fusion for hyperspectral image classification: Current trends and challenges
M Imani, H Ghassemian - Information fusion, 2020 - Elsevier
Hyperspectral images (HSIs) have a cube form containing spatial information in two
dimensions and rich spectral information in the third one. The high volume of spectral bands …
dimensions and rich spectral information in the third one. The high volume of spectral bands …
New frontiers in spectral-spatial hyperspectral image classification: The latest advances based on mathematical morphology, Markov random fields, segmentation …
In recent years, airborne and spaceborne hyperspectral imaging systems have advanced in
terms of spectral and spatial resolution, which makes the data sets they produce a valuable …
terms of spectral and spatial resolution, which makes the data sets they produce a valuable …
Hyperspectral remote sensing data analysis and future challenges
JM Bioucas-Dias, A Plaza… - … and remote sensing …, 2013 - ieeexplore.ieee.org
Hyperspectral remote sensing technology has advanced significantly in the past two
decades. Current sensors onboard airborne and spaceborne platforms cover large areas of …
decades. Current sensors onboard airborne and spaceborne platforms cover large areas of …
Advances in spectral-spatial classification of hyperspectral images
Recent advances in spectral-spatial classification of hyperspectral images are presented in
this paper. Several techniques are investigated for combining both spatial and spectral …
this paper. Several techniques are investigated for combining both spatial and spectral …