Classification of Hyperspectral Images by Gabor Filtering Based Deep Network

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

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

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

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Rotation-Based Deep Forest for Hyperspectral Imagery Classification

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Hyperspectral Image Classification via Discriminant Gabor Ensemble Filter

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

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

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

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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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 14 · see citing works

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 14 · see citing works

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 14 · see citing works

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 13 · see citing works

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 · see citing works

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 · see citing works

Spatial-Aware Network for Hyperspectral Image Classification

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

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 · see citing works

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 · see citing works

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 · see citing works

Semantic segmentation using GSAUNet

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

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

An efficient joint framework assisted by embedded feature smoother and sparse skip connection for hyperspectral image classification

Li, C., Tang, X., Shi, L., Peng, Y., & Zhou, T. (2023) · Infrared Physics & Technology · doi:10.1016/j.infrared.2023.104985 · Cited by 8 · see citing works

Spectral–spatial discriminative broad graph convolution networks for hyperspectral image classification

Wang, Z., Li, J., Zhang, T., & Yuan, S. (2022) · International Journal of Machine Learning and Cybernetics · doi:10.1007/s13042-022-01680-x · Cited by 8 · see citing works

Simplified Nonlocal Network Based on Adaptive Projection Attention Method for Hyperspectral Image Classification

Shang, R., Li, W., Zhang, W., Feng, J., Li, Y., & Jiao, L. (2022) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2022.3223508 · Cited by 8 · see citing works

Sequential Spectral-Spatial Feature Convolution Network With Self-Attention for Remote Sensing Hyperspectral Image Classification

Liu, J., Wang, H., Liu, R., Wang, S., & Liu, Y. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3508737 · Cited by 7 · see citing works

A Survey of Sampling Methods for Hyperspectral Remote Sensing: Addressing Bias Induced by Random Sampling

Decker, K. T., & Borghetti, B. J. (2025) · Remote Sensing · doi:10.3390/rs17081373 · Cited by 7 · see citing works

Fusion High-and-Low-Level Features via Ridgelet and Convolutional Neural Networks for Very High-Resolution Remote Sensing Imagery Classification

Zheng, Z., & Cao, J. (2019) · IEEE Access · doi:10.1109/access.2019.2936295 · Cited by 7 · see citing works

GhoMR: Multi-Receptive Lightweight Residual Modules for Hyperspectral Classification

Das, A., Saha, I., & Scherer, R. (2020) · Sensors · doi:10.3390/s20236823 · Cited by 7 · see citing works

Gabor filtering based deep network for hyperspectral image classification

Li, C., Shutao Li, A., Kang, X., & Lu, T. (2017) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss.2017.8127327 · Cited by 12 · see citing works

Hyperspectral images classification with Gabor filtering and feature fusion network

Han, X., Jiang, Z., Liu, Y., Zhao, J. C., & Sun, Q. (2024) · International Conference on Geology, Mapping and Remote Sensing (ICGMRS) · doi:10.1117/12.3019429

A new hyperspectral image classification method based on spatial-spectral features

Qu, S., Xiang, L., & Zhi-hua, G. (2022) · Scientific Reports · doi:10.1038/s41598-022-05422-5 · Cited by 53 · see citing works

Hyperspectral Images Classification With Gabor Filtering and Convolutional Neural Network

Chen, Y., Zhu, L., Ghamisi, P., Jia, X., Li, G., & Tang, L. (2017) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2017.2764915 · Cited by 270 · see citing works

Multi Spectral-Spatial Gabor Feature Fusion Based On End-To-End Deep Learning For Hyperspectral Image Classification

Hanachi, R., Sellami, A., Farah, I. R., & Mura, M. D. (2022) · Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing · doi:10.1109/whispers56178.2022.9955105 · Cited by 2 · see citing works