Classification of Hyperspectral Images by Gabor Filtering Based Deep Network

LIBSVM: A library for support vector machines

Chang, C.-C., & Lin, C.-J. (2011) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/1961189.1961199 · Cited by 40,918

Deep neural networks for acoustic modeling in speech recognition: the shared views of four research groups

Hinton, G., Deng, L., Yu, D., Dahl, G., Mohamed, A.-R., Jaitly, N., Senior, A., Vanhoucke, V., Nguyen, P., Sainath, T., et al. (2012) · IEEE Signal Processing Magazine · doi:10.1109/msp.2012.2205597 · Cited by 10,260

Laplacian Eigenmaps for Dimensionality Reduction and Data Representation

Belkin, M., & Niyogi, P. (2003) · Neural Computation · doi:10.1162/089976603321780317 · Cited by 7,562

A Limited Memory Algorithm for Bound Constrained Optimization

Byrd, R. H., Lu, P., Nocedal, J. M., & Zhu, C. (1995) · SIAM Journal on Scientific Computing · doi:10.1137/0916069 · Cited by 6,267

Classification of hyperspectral remote sensing images with support vector machines

Melgani, F., & Bruzzone, L. (2004) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2004.831865 · Cited by 4,426

Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches

Bioucas-Dias, J. M., Plaza, A., Dobigeon, N., Parente, M., Du, Q., Gader, P., & Chanussot, J. (2012) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2012.2194696 · Cited by 2,836

Deep learning-based classification of hyperspectral data

Chen, Y., Lin, Z., Zhao, X., Wang, G., & Gu, Y. (2014) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2014.2329330 · Cited by 2,679

Deep Learning Face Representation from Predicting 10,000 Classes

Sun, Y. J., Wang, X., & Tang, X. (2014) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2014.244 · Cited by 2,023

Gabor feature based classification using the enhanced fisher linear discriminant model for face recognition

Liu, C., & Wechsler, H. (2002) · IEEE Transactions on Image Processing · doi:10.1109/tip.2002.999679 · Cited by 1,904

Spectral–Spatial Classification of Hyperspectral Imagery with 3D Convolutional Neural Network

Li, Y., Zhang, H., & Shen, Q. (2017) · Remote Sensing · doi:10.3390/rs9010067 · Cited by 1,340

Deep Learning for Hyperspectral Image Classification: An Overview

Li, S., Song, W., Fang, L., Chen, Y., Ghamisi, P., & Benediktsson, J. A. (2019) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2019.2907932 · Cited by 2,007

Deep learning classifiers for hyperspectral imaging: A review

Paoletti, M. E., Haut, J. M., Plaza, J., & Plaza, A. (2019) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2019.09.006 · Cited by 1,144

Feature Extraction for Hyperspectral Imagery: The Evolution From Shallow to Deep: Overview and Toolbox

Rasti, B., Hong, D., Hang, R., Ghamisi, P., Kang, X., Chanussot, J., & Benediktsson, J. A. (2020) · IEEE Geoscience and Remote Sensing Magazine · doi:10.1109/mgrs.2020.2979764 · Cited by 575

Learning Compact and Discriminative Stacked Autoencoder for Hyperspectral Image Classification

Zhou, P., Han, J., Cheng, G., & Zhang, B. (2019) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2019.2893180 · Cited by 290

Feature extraction for hyperspectral image classification: a review

Kumar, B., Dikshit, O., Gupta, A., & Singh, M. K. (2020) · International Journal of Remote Sensing · doi:10.1080/01431161.2020.1736732 · Cited by 218

A Supervised Segmentation Network for Hyperspectral Image Classification

Sun, H., Zheng, X., & Lu, X. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2021.3055613 · Cited by 206

Deep Feature Fusion via Two-Stream Convolutional Neural Network for Hyperspectral Image Classification

Li, X., Ding, M., & Pižurica, A. (2019) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2019.2952758 · Cited by 192

Deep neural networks-based relevant latent representation learning for hyperspectral image classification

Sellami, A., & Tabbone, S. (2021) · Pattern Recognition · doi:10.1016/j.patcog.2021.108224 · Cited by 188

Hyperspectral image classification on insufficient-sample and feature learning using deep neural networks: A review

Wambugu, N. M., Chen, Y., Xiao, Z., Tan, K., Wei, M., Liu, X., & Li, J. (2021) · International Journal of Applied Earth Observation and Geoinformation · doi:10.1016/j.jag.2021.102603 · Cited by 163

Hyperspectral image classification using CNN with spectral and spatial features integration

Vaddi, R., & Manoharan, P. (2020) · Infrared Physics & Technology · doi:10.1016/j.infrared.2020.103296 · Cited by 154

Fusion of Dual Spatial Information for Hyperspectral Image Classification

Duan, P., Ghamisi, P., Kang, X., Rasti, B., Shutao Li, A., & Gloaguen, R. (2020) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2020.3031928 · Cited by 146

Automated Visual Defect Classification for Flat Steel Surface: A Survey

Luo, Q., Fang, X., Su, J., Zhou, J., Zhou, B., Yang, C., Liu, L., Gui, W., & Tian, L. (2020) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2020.3030167 · Cited by 148

Classification of hybrid seeds using near-infrared hyperspectral imaging technology combined with deep learning

Nie, P., Zhang, J., Feng, X., Yu, C., & He, Y. (2019) · Sensors and Actuators B Chemical · doi:10.1016/j.snb.2019.126630 · Cited by 145

Blood Cell Classification Based on Hyperspectral Imaging With Modulated Gabor and CNN

Huang, Q., Li, W., Zhang, B., Li, Q., Tao, R., & Lovell, N. H. (2019) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2019.2905623 · Cited by 115

Fusion of Multiple Edge-Preserving Operations for Hyperspectral Image Classification

Duan, P., Kang, X., Shutao Li, A., Ghamisi, P., & Benediktsson, J. A. (2019) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2019.2933588 · Cited by 111

Detection and Correction of Mislabeled Training Samples for Hyperspectral Image Classification

Kang, X., Duan, P., Xiang, X., Shutao Li, A., & Benediktsson, J. A. (2018) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2018.2823866 · Cited by 105

Lightweight Spectral–Spatial Squeeze-and- Excitation Residual Bag-of-Features Learning for Hyperspectral Classification

Roy, S. K., Chatterjee, S., Bhattacharyya, S., Chaudhuri, B. B., & Platoš, J. (2020) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2019.2961681 · Cited by 99

Spatial Density Peak Clustering for Hyperspectral Image Classification With Noisy Labels

Tu, B., Zhang, X., Kang, X., Wang, J., & Benediktsson, J. A. (2019) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2019.2896471 · Cited by 92

Density Peak-Based Noisy Label Detection for Hyperspectral Image Classification

Tu, B., Zhang, X., Kang, X., Zhang, G., & Shutao Li, A. (2018) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2018.2867444 · Cited by 90

A Novel Band Selection and Spatial Noise Reduction Method for Hyperspectral Image Classification

Fu, H., Zhang, A., Sun, G., Ren, J., Jia, X., Pan, Z., & Ma, H. (2022) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2022.3189015 · Cited by 89

Hyperspectral Anomaly Detection With Multiscale Attribute and Edge-Preserving Filters

Shutao Li, A., Zhang, K., Hao, Q., Duan, P., & Kang, X. (2018) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2018.2853705 · Cited by 79

Gaussian Pyramid Based Multiscale Feature Fusion for Hyperspectral Image Classification

Shutao Li, A., Hao, Q., Kang, X., & Benediktsson, J. A. (2018) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2018.2856741 · Cited by 78

Deep CNN With Multi-Scale Rotation Invariance Features for Ship Classification

Shi, Q., Li, W., Zhang, F., Hu, W., Sun, X., & Gao, L. (2018) · IEEE Access · doi:10.1109/access.2018.2853620 · Cited by 57

Spectral–Spatial Hyperspectral Classification via Structural-Kernel Collaborative Representation

Tu, B., Zhou, C., Liao, X., Zhang, G., & Peng, Y. (2020) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2020.2988124 · Cited by 51

Multi-view learning for hyperspectral image classification: An overview

Li, X., Liu, B., Zhang, K., Chen, H., Cao, W., Liu, W., & Tao, D. (2022) · Neurocomputing · doi:10.1016/j.neucom.2022.05.093 · Cited by 51

Semisupervised Hyperspectral Image Classification Using a Probabilistic Pseudo-Label Generation Framework

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Hyperspectral Image Classification Based on Domain Adaptation Broad Learning

Wang, H., Wang, X., Chen, C. L. P., & Cheng, Y. (2020) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2020.3001198 · Cited by 44

Hyperspectral image classification based on discriminative locality preserving broad learning system

Chu, Y., Lin, H., Yang, L., Zhang, D., Diao, Y., Fan, X., & Shen, C. (2020) · Knowledge-Based Systems · doi:10.1016/j.knosys.2020.106319 · Cited by 44

A new framework for hyperspectral image classification using Gabor embedded patch based convolution neural network

Boggavarapu, L. N. P. K., & Manoharan, P. (2020) · Infrared Physics & Technology · doi:10.1016/j.infrared.2020.103455 · Cited by 44

A Bayesian Meta-Learning-Based Method for Few-Shot Hyperspectral Image Classification

Zhang, J., Liu, L., Zhao, R., & Shi, Z. (2022) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2022.3232784 · Cited by 42

Strategies for dimensionality reduction in hyperspectral remote sensing: A comprehensive overview

Vaddi, R., Kumar, B. L. N. P., Manoharan, P., Agilandeeswari, L., & Sangeetha, V. (2024) · The Egyptian Journal of Remote Sensing and Space Science · doi:10.1016/j.ejrs.2024.01.005 · Cited by 41

Novel Cross-Resolution Feature-Level Fusion for Joint Classification of Multispectral and Panchromatic Remote Sensing Images

Liu, S., Zhao, H. M., Du, Q., Bruzzone, L., Samat, A., & Tong, X. (2021) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2021.3127710 · Cited by 41

A comprehensive systematic review of deep learning methods for hyperspectral images classification

Ranjan, P., & Girdhar, A. (2022) · International Journal of Remote Sensing · doi:10.1080/01431161.2022.2133579 · Cited by 41

A Lightweight Spectral–Spatial Feature Extraction and Fusion Network for Hyperspectral Image Classification

Chen, L.-L., Wei, Z., & Xu, Y. (2020) · Remote Sensing · doi:10.3390/rs12091395 · Cited by 38

A Shallow-to-Deep Feature Fusion Network for VHR Remote Sensing Image Classification

Liu, S., Zheng, Y., Du, Q., Bruzzone, L., Samat, A., Tong, X., Jin, Y., & Wang, C. (2022) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2022.3179288 · Cited by 37

Hyperspectral Target Detection With Macro-Micro Feature Extracted by 3-D Residual Autoencoder

Shi, Y., Li, J., Yin, Y., Xi, B., & Li, Y. (2019) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2019.2939833 · Cited by 37

Rotation-Based Deep Forest for Hyperspectral Imagery Classification

Cao, X., Li, W., Ge, Y., Zhao, J., & Jiao, L. (2019) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2019.2892117 · Cited by 36

Hyperspectral Image Classification via Discriminant Gabor Ensemble Filter

Huang, K.-K., Ren, C.-X., Liu, H., Lai, Z., Yu, Y., & Dai, D. (2021) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2021.3051141 · Cited by 35

Cross-Data Set Hyperspectral Image Classification Based on Deep Domain Adaptation

Ma, X., Mou, X., Wang, J., Liu, X., Wang, H., & Yin, B. (2019) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2019.2931730 · Cited by 34

Deep Learning Combined with Hyperspectral Imaging Technology for Variety Discrimination of Fritillaria thunbergii

Kabir, M. H., Guindo, M. L., Chen, R., Liu, F., Luo, X., & Kong, W. (2022) · Molecules · doi:10.3390/molecules27186042 · Cited by 33

A Coarse-to-Fine Method for Cloud Detection in Remote Sensing Images

Kang, X., Gao, G., Hao, Q., & Shutao Li, A. (2018) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2018.2866499 · Cited by 33

Feature Extraction via Joint Adaptive Structure Density for Hyperspectral Imagery Classification

Tu, B., Zhou, C., Jin, P., Zhang, G., & Peng, Y. (2021) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2020.3038557 · Cited by 33

Exploiting Spectral–Spatial Information Using Deep Random Forest for Hyperspectral Imagery Classification

Tong, F., & Zhang, Y. (2021) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2021.3112198 · Cited by 32

The Effect of Ground Truth on Performance Evaluation of Hyperspectral Image Classification

Shutao Li, A., Hao, Q., Gao, G., & Kang, X. (2018) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2018.2849225 · Cited by 31

Detection of apple mosaic based on hyperspectral imaging and three-dimensional Gabor

Liu, Y., Zhao, X., Song, Z., Yu, J., Jiang, D., Zhang, Y., & Chang, Q. (2024) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2024.109051 · Cited by 28

Semisupervised Classification of Hyperspectral Image Based on Graph Convolutional Broad Network

Wang, H., Cheng, Y., Chen, C. L. P., & Wang, X. (2021) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2021.3062642 · Cited by 28

Analysis for the Weakly Pareto Optimum in Multiobjective-Based Hyperspectral Band Selection

Pan, B., Shi, Z., & Xu, X. (2019) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2018.2886853 · Cited by 26

Hyperspectral Classification via Global-Local Hierarchical Weighting Fusion Network

Tu, B., He, W., He, W. P., Ou, X., & Plaza, A. (2021) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2021.3133009 · Cited by 26

Spatial‐spectral classification of hyperspectral images: a deep learning framework with Markov Random fields based modelling

Qing, C., Ruan, J., Xu, X., Ren, J., & Zabalza, J. (2018) · IET Image Processing · doi:10.1049/iet-ipr.2018.5727 · Cited by 26

A sparse tensor-based classification method of hyperspectral image

Liu, F., & Wang, Q. (2019) · Signal Processing · doi:10.1016/j.sigpro.2019.107361 · Cited by 26

Multi-view graph representation learning for hyperspectral image classification with spectral–spatial graph neural networks

Hanachi, R., Sellami, A., Farah, I. R., & Mura, M. D. (2023) · Neural Computing and Applications · doi:10.1007/s00521-023-09275-5 · Cited by 25

Spectral–Spatial Hyperspectral Image Classification Using Cascaded Markov Random Fields

Cao, X., Wang, X., Wang, D., Zhao, J., & Jiao, L. (2019) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2019.2938208 · Cited by 24

Hyperspectral image classification with discriminative manifold broad learning system

Chu, Y., Lin, H., Yang, L., Sun, S., Diao, Y., Min, C., Fan, X., & Shen, C. (2021) · Neurocomputing · doi:10.1016/j.neucom.2021.01.120 · Cited by 24

Feature Extraction Using Multitask Superpixel Auxiliary Learning for Hyperspectral Classification

Tu, B., Liao, X., Zhou, C., Chen, S., & He, W. P. (2021) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2021.3116289 · Cited by 24

Multiobjective-Based Sparse Representation Classifier for Hyperspectral Imagery Using Limited Samples

Pan, B., Shi, Z., & Xu, X. (2018) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2018.2853268 · Cited by 23

Hyperspectral Image Classification via Superpixel Correlation Coefficient Representation

Tu, B., Yang, X., Li, N., Ou, X., & He, W. P. (2018) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2018.2866901 · Cited by 23

Label Propagation Ensemble for Hyperspectral Image Classification

Zhang, Y., Cao, G., Shafique, A., & Fu, P. (2019) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2019.2926123 · Cited by 23

A Sparse Representation-Based Sample Pseudo-Labeling Method for Hyperspectral Image Classification

Cui, B., Cui, J., Lu, Y., Guo, N., & Gong, M. (2020) · Remote Sensing · doi:10.3390/rs12040664 · Cited by 23

Iterative Gaussian–Laplacian Pyramid Network for Hyperspectral Image Classification

Chang, C., Liang, C.-C., & Hu, P. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3367127 · Cited by 22

Learning a Deep Similarity Network for Hyperspectral Image Classification

Yang, B., Li, H., & Guo, Z. (2020) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2020.3041344 · Cited by 21

Ensemble of multiple CNN classifiers for HSI classification with Superpixel Smoothing

Prasanth, S., & Dash, R. (2021) · Computers & Geosciences · doi:10.1016/j.cageo.2021.104806 · Cited by 21

Modified-mean-shift-based noisy label detection for hyperspectral image classification

Bahraini, T., Azimpour, P., & Yazdi, H. S. (2021) · Computers & Geosciences · doi:10.1016/j.cageo.2021.104843 · Cited by 20

MagNet: Detecting Digital Presentation Attacks on Face Recognition

Agarwal, A., Singh, R., Mayank Vatsa, A., & Afzel Noore, B. (2021) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2021.643424 · Cited by 20

JL-GFDN: A Novel Gabor Filter-Based Deep Network Using Joint Spectral-Spatial Local Binary Pattern for Hyperspectral Image Classification

Zhang, T., Zhang, P., Zhong, W., Yang, Z., & Yang, F. (2020) · Remote Sensing · doi:10.3390/rs12122016 · Cited by 19

Local sensitive discriminative broad learning system for hyperspectral image classification

Cao, H., Song, C., Chu, Y., Zhao, C., Deng, M., & Liu, G. (2023) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2023.106307 · Cited by 18

A Novel Spectral-Spatial Singular Spectrum Analysis Technique for Near Real-Time In Situ Feature Extraction in Hyperspectral Imaging

Fu, H., Sun, G., Zabalza, J., Zhang, A., Ren, J., & Jia, X. (2020) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2020.2992230 · Cited by 18

Spectral-spatial hyperspectral image classification based on superpixel and multi-classifier fusion

Cui, B., Cui, J., Hao, S., Guo, N., & Lu, Y. (2020) · International Journal of Remote Sensing · doi:10.1080/01431161.2020.1736730 · Cited by 17

Hyperspectral Image Classification Based on a 3D Octave Convolution and 3D Multiscale Spatial Attention Network

Shi, C., Sun, J., Wang, T., & Wang, L. (2023) · Remote Sensing · doi:10.3390/rs15010257 · Cited by 17

Composite Kernel of Mutual Learning on Mid-Level Features for Hyperspectral Image Classification

Sima, H., Wang, J., Guo, P., Sun, J., Liu, H., Xu, M., & Zou, Y. (2021) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2021.3080304 · Cited by 17

Hybrid Dense Network with Dual Attention for Hyperspectral Image Classification

Zhao, J., Hu, L., Dong, Y., & Huang, L. (2021) · Remote Sensing · doi:10.3390/rs13234921 · Cited by 16

Fusion of hyperspectral and LiDAR data using sparse stacked autoencoder for land cover classification with 3D-2D convolutional neural network

Singh, M. K., Mohan, S., & Kumar, B. (2022) · Journal of Applied Remote Sensing · doi:10.1117/1.jrs.16.034523 · Cited by 16

Evrişimsel sinir ağı ve iki-boyutlu karmaşık gabor dönüşümü kullanılarak hiperspektral görüntü sınıflandırma

Hanbay, K. (2019) · Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi · doi:10.17341/gazimmfd.479086 · Cited by 15

Dual Sparse Representation Graph-Based Copropagation for Semisupervised Hyperspectral Image Classification

Zhang, Y., Cao, G., Wang, B., Li, X., Amoako, P. Y. O., & Shafique, A. (2021) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2020.3046780 · Cited by 15

Computer Vision-Based Kidney’s (HK-2) Damaged Cells Classification with Reconfigurable Hardware Accelerator (FPGA)

Ghani, A., Hodeify, R. F., See, C. H., Keates, S., Lee, D.-J., & Bouridane, A. (2022) · Electronics · doi:10.3390/electronics11244234 · Cited by 14

A new deep learning approach for classification of hyperspectral images: feature and decision level fusion of spectral and spatial features in multiscale CNN

Sharifi, O., Mokhtarzadeh, M., & Beirami, B. A. (2021) · Geocarto International · doi:10.1080/10106049.2021.1882006 · Cited by 14

Pseudo Complex-Valued Deformable ConvLSTM Neural Network With Mutual Attention Learning for Hyperspectral Image Classification

Hu, W.-S., Li, H.-C., Wang, R., Gao, F., Du, Q., & Plaza, A. (2022) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2022.3188791 · Cited by 15

Bayesian Deep Learning for Hyperspectral Image Classification With Low Uncertainty

He, X. S., Chen, Y., & Huang, L. (2023) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2023.3257865 · Cited by 15

Discriminative spatial-temporal feature learning for modeling network intrusion detection systems

Wanjau, S. K., Wambugu, G. M., Oirere, A. M., & Muketha, G. M. (2023) · Journal of Computer Security · doi:10.3233/jcs-220031 · Cited by 19

Distribution-Aware and Class-Adaptive Aggregation for Few-Shot Hyperspectral Image Classification

Guo, Y., Fan, B., Feng, Y., Jia, X., & He, M. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3432734 · Cited by 14

Feature extraction from hyperspectral images using learned edge structures

Zhang, Y., Kang, X., Shutao Li, A., Duan, P., & Benediktsson, J. A. (2018) · Remote Sensing Letters · doi:10.1080/2150704x.2018.1524993 · Cited by 13

Residual networks with multi-attention mechanism for hyperspectral image classification

Shao, Y., Lan, J., Liang, Y., & Hu, J. H. (2021) · Arabian Journal of Geosciences · doi:10.1007/s12517-021-06516-6 · Cited by 12

Spatial-Aware Network for Hyperspectral Image Classification

Wei, Y., & Zhou, Y. (2021) · Remote Sensing · doi:10.3390/rs13163232 · Cited by 11

ODPA-CNN: One Dimensional Parallel Atrous Convolution Neural Network for Band-Selective Hyperspectral Image Classification

Kang, B., Park, I., Ok, C.-M., & Kim, S. (2021) · Applied Sciences · doi:10.3390/app12010174 · Cited by 10

Hyperspectral image classification using multi-task feature leverage with multi-variant deep learning

Jayapriya, K., Jacob, I. J., & Darney, P. E. (2020) · Earth Science Informatics · doi:10.1007/s12145-020-00485-2 · Cited by 10

Multi-type spectral spatial feature for hyperspectral image classification

Yuan, Y., & Jin, M. (2021) · Neurocomputing · doi:10.1016/j.neucom.2021.12.055 · Cited by 10

Semantic segmentation using GSAUNet

Nemade, S. B., & Sonavane, S. P. (2022) · ICT Express · doi:10.1016/j.icte.2022.09.007 · Cited by 9

Spatial-Spectral Random Patches Network for Classification of Hyperspectral Images

Beirami, B. A., & Mokhtarzade, M. (2019) · Traitement du signal · doi:10.18280/ts.360504 · Cited by 9

Image Large Rotation and Scale Estimation Using the Gabor Filter

Tang, W., Jia, F., & Wang, X. (2022) · Electronics · doi:10.3390/electronics11213471 · Cited by 9

Object-based classification of hyperspectral images based on weighted genetic algorithm and deep learning model

Akbari, D., & Akbari, V. (2023) · Applied Geomatics · doi:10.1007/s12518-023-00500-3 · Cited by 9

Relative Total Variation Structure Analysis-Based Fusion Method for Hyperspectral and LiDAR Data Classification

Quan, Y., Tong, Y., Feng, W., Dauphin, G., Huang, W., Zhu, W., & Xing, M. (2021) · Remote Sensing · doi:10.3390/rs13061143 · Cited by 9

Texture Pattern Separation for Hyperspectral Image Classification

Tu, B., Wang, J., Zhang, G., Zhang, X., & He, W. P. (2019) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2019.2924930 · Cited by 9

Onboard target detection in hyperspectral image based on deep learning with FPGA implementation

Shibi, C. S., & Gayathri, R. (2021) · Microprocessors and Microsystems · doi:10.1016/j.micpro.2021.104313 · Cited by 8

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