Low-rank and sparse representation for hyperspectral image processing: A review

J Peng, W Sun, HC Li, W Li, X Meng… - IEEE Geoscience and …, 2021‏ - ieeexplore.ieee.org
Combining rich spectral and spatial information, a hyperspectral image (HSI) can provide a
more comprehensive characterization of the Earth's surface. To better exploit HSIs, a large …

Recent advances on spectral–spatial hyperspectral image classification: An overview and new guidelines

L He, J Li, C Liu, S Li - IEEE Transactions on Geoscience and …, 2017‏ - ieeexplore.ieee.org
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 …

[HTML][HTML] Improved transformer net for hyperspectral image classification

Y Qing, W Liu, L Feng, W Gao - Remote Sensing, 2021‏ - mdpi.com
In recent years, deep learning has been successfully applied to hyperspectral image
classification (HSI) problems, with several convolutional neural network (CNN) based …

HSI-BERT: Hyperspectral image classification using the bidirectional encoder representation from transformers

J He, L Zhao, H Yang, M Zhang… - IEEE Transactions on …, 2019‏ - ieeexplore.ieee.org
Deep learning methods have been widely used in hyperspectral image classification and
have achieved state-of-the-art performance. Nonetheless, the existing deep learning …

Diverse region-based CNN for hyperspectral image classification

M Zhang, W Li, Q Du - IEEE Transactions on Image Processing, 2018‏ - ieeexplore.ieee.org
Convolutional neural network (CNN) is of great interest in machine learning and has
demonstrated excellent performance in hyperspectral image classification. In this paper, we …

[HTML][HTML] A deep learning-based approach for automated yellow rust disease detection from high-resolution hyperspectral UAV images

X Zhang, L Han, Y Dong, Y Shi, W Huang, L Han… - Remote Sensing, 2019‏ - mdpi.com
Yellow rust in winter wheat is a widespread and serious fungal disease, resulting in
significant yield losses globally. Effective monitoring and accurate detection of yellow rust …

Deep learning-based classification of hyperspectral data

Y Chen, Z Lin, X Zhao, G Wang… - IEEE Journal of Selected …, 2014‏ - ieeexplore.ieee.org
Classification is one of the most popular topics in hyperspectral remote sensing. In the last
two decades, a huge number of methods were proposed to deal with the hyperspectral data …

Spectral–spatial classification of hyperspectral data based on deep belief network

Y Chen, X Zhao, X Jia - IEEE journal of selected topics in …, 2015‏ - ieeexplore.ieee.org
Hyperspectral data classification is a hot topic in remote sensing community. In recent years,
significant effort has been focused on this issue. However, most of the methods extract the …

Hyperspectral image classification: Potentials, challenges, and future directions

D Datta, PK Mallick, AK Bhoi, MF Ijaz… - Computational …, 2022‏ - Wiley Online Library
Recent imaging science and technology discoveries have considered hyperspectral
imagery and remote sensing. The current intelligent technologies, such as support vector …

Spectral–spatial classification of hyperspectral images using deep convolutional neural networks

J Yue, W Zhao, S Mao, H Liu - Remote Sensing Letters, 2015‏ - Taylor & Francis
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 …