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Zheng, K.[Ke],
Gao, L.R.[Lian-Ru],
Zhang, B.[Bing],
Yang, D.[Dong],
Ren, J.C.[Jin-Chang],
Multiscale Spatial-Spectral Convolutional Network with Image-Based
Framework for Hyperspectral Imagery Classification,
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DOI Link
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Yu, H.Y.[Hao-Yang],
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Zhuang, L.[Lina],
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Global Spatial and Local Spectral Similarity-Based Manifold Learning
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IEEE DOI
2005
Hyperspectral imaging, Dictionaries, Manifolds, Testing, Correlation,
Task analysis, Classification, group sparse representation (GSR),
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Fusion of PCA and Segmented-PCA Domain Multiscale 2-D-SSA for
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2112
Feature extraction, Principal component analysis,
Covariance matrices, Support vector machines, Deep learning,
multiscale 2-D-singular spectrum analysis (2-D-SSA)
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Gao, L.R.[Lian-Ru],
Hyperspectral Imagery Classification Based on Multiscale
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2010
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Hyperspectral Image Classification Based on a Shuffled Group
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Zhao, H.M.[Hui-Min],
SpaSSA: Superpixelwise Adaptive SSA for Unsupervised Spatial-Spectral
Feature Extraction in Hyperspectral Image,
Cyber(52), No. 7, July 2022, pp. 6158-6169.
IEEE DOI
2207
Feature extraction, Data mining, Trajectory, Spectral analysis, Sun,
Principal component analysis, Oceanography, Feature extraction,
superpixelwise adaptive SSA (SpaSSA)
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0501
See also Multisource remote sensing data classification based on consensus and pruning.
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Fauvel, M.,
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Spectral and Spatial Classification of Hyperspectral Data Using SVMs
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GeoRS(46), No. 11, November 2008, pp. 3804-3814.
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0812
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Tarabalka, Y.[Yuliya],
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Spectral-Spatial Classification of Hyperspectral Imagery Based on
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GeoRS(47), No. 8, August 2009, pp. 2973-2987.
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0907
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Ghamisi, P.,
Benediktsson, J.A.,
Sveinsson, J.R.,
Automatic Spectral-Spatial Classification Framework Based on
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GeoRS(52), No. 9, September 2014, pp. 5771-5782.
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1407
data reduction
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Ghamisi, P.,
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Benediktsson, J.A.,
A Survey on Spectral-Spatial Classification Techniques Based on
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1502
geophysical image processing
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Ghamisi, P.,
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Ulfarsson, M.O.,
Spectral-Spatial Classification of Hyperspectral Images Based on
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GeoRS(52), No. 5, May 2014, pp. 2565-2574.
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1403
Hidden Markov random field (HMRF)
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Yu, H.Y.[Hao-Yang],
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Li, S.S.[Shan Shan],
Zhang, B.[Bing],
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Al-khafaji, S.L.,
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1712
Cameras, Feature extraction, Hyperspectral imaging,
Image resolution, Transforms,
spectral-spatial feature extraction
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Tu, B.[Bing],
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Zhao, G.,
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Hyperspectral Image Classification via Superpixel Spectral Metrics
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IEEE DOI
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Training, Measurement, Image segmentation, Entropy,
Hyperspectral imaging, Shape, Hyperspectral image (HSI),
spectral information divergence (SID)
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Tu, B.[Bing],
Li, N.Y.[Nan-Ying],
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JVCIR(56), 2018, pp. 160-166.
Elsevier DOI
1811
Hyperspectral image, Superpixel, Joint sparse representation,
Correlation coefficient
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Tu, B.[Bing],
Li, N.Y.[Nan-Ying],
Fang, L.Y.[Le-Yuan],
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Wu, J.H.[Jian-Hui],
Hyperspectral image classification with a class-dependent
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Elsevier DOI
1906
Hyperspectral image, Spectral angle mapper,
Spectral information divergence, Joint sparse representation,
Local mean-based nearest neighbors
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Yang, G.[Gan],
Wang, Z.H.[Zhao-Hui],
Light-Weight Self-Supervised Contrastive Learning Network For Small
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ICIP24(856-861)
IEEE DOI
2411
Training, Deep learning, Contrastive learning, Data augmentation,
Feature extraction, Proposals, Labeling, small sample
BibRef
Li, N.Y.[Ning-Yang],
Wang, Z.H.[Zhao-Hui],
Spectral-Spatial Fused Attention Network for Hyperspectral Image
Classification,
ICIP21(3832-3836)
IEEE DOI
2201
Deep learning, Correlation, Redundancy, Feature extraction,
Robustness, Proposals, Hyperspectral image classification, spatial features
BibRef
Fang, L.Y.[Le-Yuan],
Li, S.T.[Shu-Tao],
Duan, W.[Wuhui],
Ren, J.C.[Jin-Chang],
Benediktsson, J.A.[Jón Atli],
Classification of Hyperspectral Images by Exploiting Spectral-Spatial
Information of Superpixel via Multiple Kernels,
GeoRS(53), No. 12, December 2015, pp. 6663-6674.
IEEE DOI
1512
geophysical image processing
BibRef
Zhang, S.Z.[Shu-Zhen],
Li, S.T.[Shu-Tao],
Fu, W.[Wei],
Fang, L.Y.[Lei-Yuan],
Multiscale Superpixel-Based Sparse Representation for Hyperspectral
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RS(9), No. 2, 2017, pp. xx-yy.
DOI Link
1703
BibRef
Yue, J.[Jun],
Fang, L.Y.[Le-Yuan],
He, M.[Min],
Spectral-Spatial Latent Reconstruction for Open-Set Hyperspectral
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IP(31), 2022, pp. 5227-5241.
IEEE DOI
2208
Feature extraction, Image reconstruction, Training,
Hyperspectral imaging, Calibration, Convolution,
open-set environment
BibRef
Mou, L.C.[Li-Chao],
Lu, X.Q.[Xiao-Qiang],
Li, X.L.[Xue-Long],
Zhua, X.X.[Xiao Xiang],
Nonlocal Graph Convolutional Networks for Hyperspectral Image
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GeoRS(58), No. 12, December 2020, pp. 8246-8257.
IEEE DOI
2012
Hyperspectral imaging, Convolution, Task analysis,
Recurrent neural networks, Semisupervised learning,
semisupervised learning
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Fang, L.Y.[Le-Yuan],
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Kang, X.D.[Xu-Dong],
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Spectral-Spatial Hyperspectral Image Classification via Multiscale
Adaptive Sparse Representation,
GeoRS(52), No. 12, December 2014, pp. 7738-7749.
IEEE DOI
1410
geophysical image processing
See also Class-Specific Sparse Multiple Kernel Learning for Spectral-Spatial Hyperspectral Image Classification.
BibRef
Sun, H.[Hao],
Zheng, X.T.[Xiang-Tao],
Lu, X.Q.[Xiao-Qiang],
Wu, S.Y.[Si-Yuan],
Spectral-Spatial Attention Network for Hyperspectral Image
Classification,
GeoRS(58), No. 5, May 2020, pp. 3232-3245.
IEEE DOI
2005
Feature extraction, Hyperspectral imaging, Convolution, Training,
Imaging, Sun, Attention, convolutional neural network (CNN),
spectral-spatial feature extraction
See also Hyperspectral Image Super-Resolution with Self-Supervised Spectral-Spatial Residual Network.
BibRef
Zheng, X.T.[Xiang-Tao],
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Lu, X.Q.[Xiao-Qiang],
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Rotation-Invariant Attention Network for Hyperspectral Image
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IP(31), 2022, pp. 4251-4265.
IEEE DOI
2207
Feature extraction, Convolution, Kernel, Imaging,
Hyperspectral imaging, Interference, Data mining,
attention mechanism
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Hong, Q.Q.[Qing-Qing],
Zhong, X.Y.[Xin-Yi],
Chen, W.T.[Wei-Tong],
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Li, B.[Bin],
Sun, H.[Hao],
Yang, T.B.[Tian-Bao],
Tan, C.W.[Chang-Wei],
SATNet: A Spatial Attention Based Network for Hyperspectral Image
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RS(14), No. 22, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Hong, Q.Q.[Qing-Qing],
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Chen, W.T.[Wei-Tong],
Zhang, Z.H.[Zheng-Hua],
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Hyperspectral Image Classification Network Based on 3D Octave
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DOI Link
2312
BibRef
Duan, P.[Puhong],
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Gloaguen, R.[Richard],
Fusion of Dual Spatial Information for Hyperspectral Image
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IEEE DOI
2109
Support vector machines, Smoothing methods, Fuses, Imaging,
Feature extraction, Minerals, Task analysis, Decision fusion,
structural profile (SP)
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Tu, B.[Bing],
Zhang, X.F.[Xiao-Fei],
Kang, X.D.[Xu-Dong],
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Li, S.T.[Shu-Tao],
Density Peak-Based Noisy Label Detection for Hyperspectral Image
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GeoRS(57), No. 3, March 2019, pp. 1573-1584.
IEEE DOI
1903
hyperspectral imaging, image classification, pattern clustering,
remote sensing, support vector machines,
support vector machines (SVMs)
BibRef
Fu, W.,
Li, S.T.[Shu-Tao],
Fang, L.Y.[Le-Yuan],
Benediktsson, J.A.[Jón Atli],
Contextual Online Dictionary Learning for Hyperspectral Image
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GeoRS(56), No. 3, March 2018, pp. 1336-1347.
IEEE DOI
1804
hyperspectral imaging, image classification,
image representation, learning (artificial intelligence),
sparse representation (SR)
BibRef
Tu, B.[Bing],
Zhang, X.F.[Xiao-Fei],
Kang, X.D.[Xu-Dong],
Wang, J.P.[Jin-Ping],
Benediktsson, J.A.[Jón Atli],
Spatial Density Peak Clustering for Hyperspectral Image
Classification With Noisy Labels,
GeoRS(57), No. 7, July 2019, pp. 5085-5097.
IEEE DOI
1907
Noise measurement, Training, Correlation, Clustering algorithms,
Hyperspectral imaging, Labeling, Density peak (DP) clustering,
support vector machines (SVMs)
BibRef
Jia, S.[Sen],
Zhuang, J.Y.[Jia-Yue],
Deng, L.[Lin],
Zhu, J.S.[Jia-Song],
Xu, M.[Meng],
Zhou, J.[Jun],
Jia, X.P.[Xiu-Ping],
3-D Gaussian-Gabor Feature Extraction and Selection for Hyperspectral
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GeoRS(57), No. 11, November 2019, pp. 8813-8826.
IEEE DOI
1911
Hyperspectral imaging, Feature extraction,
Principal component analysis, Training, Task analysis, Redundancy,
hyperspectral imagery
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Deng, B.[Bin],
Jia, S.[Sen],
Shi, D.M.[Da-Ming],
Deep Metric Learning-Based Feature Embedding for Hyperspectral Image
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IEEE DOI
2001
Measurement, Training, Task analysis, Adaptation models,
Feature extraction, Hyperspectral imaging,
small sample set (3S) classification
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Jia, S.[Sen],
Deng, B.[Bin],
Xie, H.M.[Hui-Min],
Deng, L.[Lin],
A Gabor feature fusion framework for hyperspectral imagery
classification,
ICIP17(2394-2397)
IEEE DOI
1803
Data mining, Feature extraction, Hamming distance,
Hyperspectral imaging, Training,
feature fusion
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Zhu, J.,
Hu, J.,
Jia, S.,
Jia, X.,
Li, Q.,
Multiple 3-D Feature Fusion Framework for Hyperspectral Image
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GeoRS(56), No. 4, April 2018, pp. 1873-1886.
IEEE DOI
1804
Feature extraction, Hyperspectral imaging, Shape,
Surface morphology, Wavelet transforms, Feature fusion,
sparse representation
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Chen, Y.S.[Yu-Shi],
Huang, L.B.[Ling-Bo],
Zhu, L.[Lin],
Yokoya, N.[Naoto],
Jia, X.P.[Xiu-Ping],
Fine-Grained Classification of Hyperspectral Imagery Based on Deep
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BibRef
Lu, T.[Ting],
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Fang, L.Y.[Le-Yuan],
Jia, X.P.[Xiu-Ping],
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From Subpixel to Superpixel: A Novel Fusion Framework for
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GeoRS(55), No. 8, August 2017, pp. 4398-4411.
IEEE DOI
1708
Data mining, Feature extraction, Geometry, Hyperspectral imaging,
Probabilistic logic, Support vector machines, Decision fusion,
feature fusion, hyperspectral image (HSI) classification, pixel,
subpixel, superpixel
BibRef
Jia, S.[Sen],
Deng, B.[Bin],
Zhu, J.S.[Jia-Song],
Jia, X.P.[Xiu-Ping],
Li, Q.Q.[Qing-Quan],
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GeoRS(55), No. 5, May 2017, pp. 2575-2588.
IEEE DOI
1705
filtering theory, hyperspectral imaging, remote sensing by radar,
Gabor filters, classification performance,
computational complexity, hyperspectral image classification,
pixel-based spatial-spectral Schroedinger eigenmaps method,
superpixel-based multitask learning framework,
BibRef
Jia, S.[Sen],
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Zhu, J.S.[Jia-Song],
Jia, X.P.[Xiu-Ping],
Li, Q.Q.[Qing-Quan],
Local Binary Pattern-Based Hyperspectral Image Classification With
Superpixel Guidance,
GeoRS(56), No. 2, February 2018, pp. 749-759.
IEEE DOI
1802
Feature extraction, Hyperspectral imaging, Image segmentation,
Merging, Support vector machines, Training,
superpixel
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Jia, S.[Sen],
Wu, K.L.[Kui-Lin],
Zhu, J.S.[Jia-Song],
Jia, X.P.[Xiu-Ping],
Spectral-Spatial Gabor Surface Feature Fusion Approach for
Hyperspectral Imagery Classification,
GeoRS(57), No. 2, February 2019, pp. 1142-1154.
IEEE DOI
1901
Hyperspectral imaging, Feature extraction, Clustering algorithms,
Support vector machines, Image segmentation, Data mining,
hyperspectral imagery classification
BibRef
Jia, S.[Sen],
Deng, X.L.[Xiang-Long],
Zhu, J.S.[Jia-Song],
Xu, M.[Meng],
Zhou, J.[Jun],
Jia, X.P.[Xiu-Ping],
Collaborative Representation-Based Multiscale Superpixel Fusion for
Hyperspectral Image Classification,
GeoRS(57), No. 10, October 2019, pp. 7770-7784.
IEEE DOI
1910
feature extraction, Gabor filters, geophysical image processing,
hyperspectral imaging, image classification, image fusion,
superpixel segmentation
BibRef
Jia, S.[Sen],
Shen, L.L.[Lin-Lin],
Li, Q.Q.[Qing-Quan],
Gabor Feature-Based Collaborative Representation for Hyperspectral
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GeoRS(53), No. 2, February 2015, pp. 1118-1129.
IEEE DOI
1411
compressed sensing
BibRef
Shen, L.L.[Lin-Lin],
Jia, S.[Sen],
Three-Dimensional Gabor Wavelets for Pixel-Based Hyperspectral Imagery
Classification,
GeoRS(49), No. 12, December 2011, pp. 5039-5046.
IEEE DOI
1201
BibRef
Jia, S.[Sen],
Shen, L.L.[Lin-Lin],
Zhu, J.,
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A 3-D Gabor Phase-Based Coding and Matching Framework for
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Cyber(48), No. 4, April 2018, pp. 1176-1188.
IEEE DOI
1804
Data mining, Feature extraction, Hyperspectral imaging,
Image coding, Training, Wavelet transforms, Gabor wavelets,
phase coding
BibRef
Jia, S.[Sen],
Deng, X.L.[Xiang-Long],
Xu, M.[Meng],
Zhou, J.[Jun],
Jia, X.P.[Xiu-Ping],
Superpixel-Level Weighted Label Propagation for Hyperspectral Image
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GeoRS(58), No. 7, July 2020, pp. 5077-5091.
IEEE DOI
2006
Hyperspectral imaging, Semisupervised learning,
Image segmentation, Training, Erbium, Tuning, Hyperspectral image,
superpixel segmentation
BibRef
Jia, S.,
Xie, H.,
Deng, X.,
Extended Morphological Profile-based Gabor Wavelets for Hyperspectral
Image Classification,
ICPR18(782-787)
IEEE DOI
1812
Feature extraction, Hyperspectral imaging,
Data mining, Wavelet transforms, Surface waves
BibRef
Jia, S.[Sen],
Zhao, Q.Q.[Qing-Qing],
Zhuang, J.Y.[Jia-Yue],
Tang, D.D.[Ding-Ding],
Long, Y.Q.[Ya-Qian],
Xu, M.[Meng],
Zhou, J.[Jun],
Li, Q.Q.[Qing-Quan],
Flexible Gabor-Based Superpixel-Level Unsupervised LDA for
Hyperspectral Image Classification,
GeoRS(59), No. 12, December 2021, pp. 10394-10409.
IEEE DOI
2112
Feature extraction, Hyperspectral imaging, Training,
Image segmentation, Linear discriminant analysis, Data mining,
superpixel segmentation
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Jia, S.[Sen],
Hu, J.[Jie],
Zhu, J.S.[Jia-Song],
Jia, X.P.[Xiu-Ping],
Li, Q.Q.[Qing-Quan],
Three-Dimensional Local Binary Patterns for Hyperspectral Imagery
Classification,
GeoRS(55), No. 4, April 2017, pp. 2399-2413.
IEEE DOI
1704
feature extraction
BibRef
Jia, S.[Sen],
Hu, J.[Jie],
Xie, Y.[Yao],
Shen, L.L.[Lin-Lin],
Jia, X.P.[Xiu-Ping],
Li, Q.Q.[Qing-Quan],
Gabor Cube Selection Based Multitask Joint Sparse Representation for
Hyperspectral Image Classification,
GeoRS(54), No. 6, June 2016, pp. 3174-3187.
IEEE DOI
1606
Gabor filters
BibRef
Huang, L.B.[Ling-Bo],
Chen, Y.S.[Yu-Shi],
He, X.[Xin],
Ghamisi, P.[Pedram],
Supervised Contrastive Learning-Based Classification for
Hyperspectral Image,
RS(14), No. 21, 2022, pp. xx-yy.
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2212
BibRef
Huang, L.B.[Ling-Bo],
Chen, Y.S.[Yu-Shi],
He, X.[Xin],
Weakly Supervised Classification of Hyperspectral Image Based on
Complementary Learning,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Othman, H.,
Qian, S.E.,
Noise Reduction of Hyperspectral Imagery Using Hybrid Spatial-Spectral
Derivative-Domain Wavelet Shrinkage,
GeoRS(44), No. 2, February 2006, pp. 397-408.
IEEE DOI
0602
BibRef
Liu, J.,
Lu, W.,
A Probabilistic Framework for Spectral-Spatial Classification of
Hyperspectral Images,
GeoRS(54), No. 9, September 2016, pp. 5375-5384.
IEEE DOI
1609
estimation theory
BibRef
Zhou, Y.C.[Yi-Cong],
Peng, J.T.[Jiang-Tao],
Chen, C.L.P.,
Dimension Reduction Using Spatial and Spectral Regularized Local
Discriminant Embedding for Hyperspectral Image Classification,
GeoRS(53), No. 2, February 2015, pp. 1082-1095.
IEEE DOI
1411
geophysical image processing
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Zhang, J.[Jie],
Zhang, Y.S.[Yong-Shan],
Zhou, Y.C.[Yi-Cong],
Quantum-Inspired Spectral-Spatial Pyramid Network for Hyperspectral
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CVPR23(9925-9934)
IEEE DOI
2309
BibRef
Wei, Y.T.[Yan-Tao],
Zhou, Y.C.[Yi-Cong],
Spatial-Aware Network for Hyperspectral Image Classification,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Wei, Y.T.[Yan-Tao],
Zhou, Y.C.[Yi-Cong],
Li, H.[Hong],
Spectral-Spatial Response for Hyperspectral Image Classification,
RS(9), No. 3, 2017, pp. xx-yy.
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1704
BibRef
Li, H.[Hong],
Song, Y.[Yalong],
Chen, C.L.P.[C.L. Philip],
Hyperspectral Image Classification Based on Multiscale Spatial
Information Fusion,
GeoRS(55), No. 9, September 2017, pp. 5302-5312.
IEEE DOI
1709
hyperspectral imaging, image classification, image fusion,
HSI classification, L1-DE, MSIF,
hyperspectral image classification, local 1D embedding,
multiscale spatial information fusion, multiscale strategy,
BibRef
Sun, Q.[Qian],
Zhao, G.R.[Guang-Rui],
Fang, Y.[Yu],
Fang, C.R.[Chen-Rong],
Sun, L.[Le],
Li, X.Y.[Xing-Ying],
MEA-EFFormer: Multiscale Efficient Attention with Enhanced Feature
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RS(16), No. 9, 2024, pp. 1560.
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BibRef
Lu, W.[Wen],
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Sun, L.[Le],
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Spectral-Spatial Feature Extraction for Hyperspectral Image
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DOI Link
2401
BibRef
Wang, X.Y.[Xin-Yu],
Sun, L.[Le],
Lu, C.H.[Chu-Han],
Li, B.Z.[Bao-Zhu],
A Novel Transformer Network with a CNN-Enhanced Cross-Attention
Mechanism for Hyperspectral Image Classification,
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2404
BibRef
Liu, J.J.[Jian-Jun],
Xiao, Z.Y.[Zhi-Yong],
Chen, Y.F.[Yu-Feng],
Yang, J.L.[Jin-Long],
Spatial-Spectral Graph Regularized Kernel Sparse Representation for
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Image edge detection, Hyperspectral imaging, Libraries,
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spatial information
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Adaptation models
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1703
Feature extraction
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Markov processes
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1903
hyperspectral imaging, image restoration, optimisation,
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Complexity theory, Correlation, Hyperspectral imaging, Libraries,
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2012
Hyperspectral imaging, Libraries, Sparse matrices, Collaboration,
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geophysical image processing
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Feature extraction, Harmonic analysis, Kernel,
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Gabor filters, feature extraction, hyperspectral imaging,
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feature extraction, hyperspectral imaging, image classification,
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convolution, feature
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2301
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Ma, B.[Boran],
Wang, L.G.[Li-Guo],
Wang, H.[Heng],
Hyperspectral Image Classification Based on Two-Branch Multiscale
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RS(16), No. 11, 2024, pp. 1888.
DOI Link
2406
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Pan, H.Z.[Hai-Zhu],
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Ge, H.M.[Hai-Miao],
Liu, M.[Moqi],
Shi, C.P.[Cui-Ping],
Hyperspectral Image Classification Based on Multiscale Hybrid
Networks and Attention Mechanisms,
RS(15), No. 11, 2023, pp. 2720.
DOI Link
2306
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Liu, D.X.[Dong-Xu],
Han, G.L.[Guang-Liang],
Liu, P.X.[Pei-Xun],
Yang, H.[Hang],
Chen, D.B.[Dian-Bing],
Li, Q.Q.[Qing-Qing],
Wu, J.J.[Jia-Jia],
Wang, Y.[Yirui],
A Discriminative Spectral-Spatial-Semantic Feature Network Based on
Shuffle and Frequency Attention Mechanisms for Hyperspectral Image
Classification,
RS(14), No. 11, 2022, pp. xx-yy.
DOI Link
2206
BibRef
Liu, Z.C.[Zhi-Chao],
Han, G.L.[Guang-Liang],
Yang, H.[Hang],
Liu, P.X.[Pei-Xun],
Chen, D.B.[Dian-Bing],
Liu, D.X.[Dong-Xu],
Deng, A.[Anping],
CCC-SSA-UNet: U-Shaped Pansharpening Network with Channel
Cross-Concatenation and Spatial-Spectral Attention Mechanism for
Hyperspectral Image Super-Resolution,
RS(15), No. 17, 2023, pp. 4328.
DOI Link
2310
BibRef
Liu, D.X.[Dong-Xu],
Wang, Y.R.[Yi-Rui],
Liu, P.X.[Pei-Xun],
Li, Q.Q.[Qing-Qing],
Yang, H.[Hang],
Chen, D.B.[Dian-Bing],
Liu, Z.C.[Zhi-Chao],
Han, G.L.[Guang-Liang],
A Multibranch Crossover Feature Attention Network for Hyperspectral
Image Classification,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link
2212
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Liu, D.X.[Dong-Xu],
Han, G.L.[Guang-Liang],
Liu, P.X.[Pei-Xun],
Wang, Y.R.[Yi-Rui],
Yang, H.[Hang],
Chen, D.B.[Dian-Bing],
Li, Q.Q.[Qing-Qing],
Wu, J.J.[Jia-Jia],
A Hybrid-Order Spectral-Spatial Feature Network for Hyperspectral
Image Classification,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Liu, D.X.[Dong-Xu],
Wang, Y.[Yirui],
Liu, P.X.[Pei-Xun],
Li, Q.Q.[Qing-Qing],
Yang, H.[Hang],
Chen, D.B.[Dian-Bing],
Liu, Z.C.[Zhi-Chao],
Han, G.L.[Guang-Liang],
A Multiscale Cross Interaction Attention Network for Hyperspectral
Image Classification,
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DOI Link
2301
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Liu, D.X.[Dong-Xu],
Li, Q.Q.[Qing-Qing],
Li, M.H.[Mei-Hui],
Zhang, J.L.[Jian-Lin],
A Decompressed Spectral-Spatial Multiscale Semantic Feature Network
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DOI Link
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Yang, J.Q.[Jia-Qi],
Du, B.[Bo],
Xu, Y.H.[Yong-Hao],
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Can Spectral Information Work While Extracting Spatial Distribution?:
An Online Spectral Information Compensation Network for HSI
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IEEE DOI
2305
Feature extraction, Data mining, Filling, Kernel, Task analysis,
Information retrieval, multi-scale features
BibRef
Liu, D.X.[Dong-Xu],
Shao, T.[Tao],
Qi, G.L.[Guang-Lin],
Li, M.H.[Mei-Hui],
Zhang, J.L.[Jian-Lin],
A Hybrid-Scale Feature Enhancement Network for Hyperspectral Image
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RS(16), No. 1, 2024, pp. xx-yy.
DOI Link
2401
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Ma, Y.X.[Yun-Xuan],
Lan, Y.[Yan],
Xie, Y.K.[Ya-Kun],
Yu, L.X.[Lan-Xin],
Chen, C.[Chen],
Wu, Y.S.[Yu-Song],
Dai, X.A.[Xiao-Ai],
A Spatial-Spectral Transformer for Hyperspectral Image Classification
Based on Global Dependencies of Multi-Scale Features,
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DOI Link
2402
BibRef
Gao, Q.[Qi],
Yin, M.F.[Ming-Feng],
Wu, X.[Xiang],
Liu, D.[Di],
Bo, Y.M.[Yu-Ming],
Online Multi-Scale Classification and Global Feature Modulation for
Robust Visual Tracking,
CirSysVideo(34), No. 7, July 2024, pp. 5321-5334.
IEEE DOI
2407
Visualization, Target tracking, Accuracy, Fuses, Modulation,
Transformers, Real-time systems, Visual object tracking,
global feature modulation
BibRef
Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Hyperspectral Target Detection .