14.1.10.4 Few Shot Learning for Remote Sensing Applications, Hyperspectral Data

Chapter Contents (Back)
Small Sample Size. Few-Shot Learning. Remote Sensing. Hyperspectral.

Kim, J.[Joseph], Chi, M.M.[Ming-Min],
SAFFNet: Self-Attention-Based Feature Fusion Network for Remote Sensing Few-Shot Scene Classification,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link 2107
BibRef

Shi, Y.Z.[Yan-Zi], Li, J.J.[Jiao-Jiao], Li, Y.S.[Yun-Song], Du, Q.[Qian],
Sensor-Independent Hyperspectral Target Detection With Semisupervised Domain Adaptive Few-Shot Learning,
GeoRS(59), No. 8, August 2021, pp. 6894-6906.
IEEE DOI 2108
Object detection, Hyperspectral imaging, Feature extraction, Adaptation models, Sensors, Task analysis, sensor-independent hyperspectral target detection (SIHTD) BibRef

Zeng, Q.J.[Qing-Jie], Geng, J.[Jie], Huang, K.[Kai], Jiang, W.[Wen], Guo, J.[Jun],
Prototype Calibration with Feature Generation for Few-Shot Remote Sensing Image Scene Classification,
RS(13), No. 14, 2021, pp. xx-yy.
DOI Link 2107
BibRef

Jiang, N.[Nan], Shi, H.W.[Hao-Wen], Geng, J.[Jie],
Multi-Scale Graph-Based Feature Fusion for Few-Shot Remote Sensing Image Scene Classification,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Zeng, Q.J.[Qing-Jie], Geng, J.[Jie],
Task-specific contrastive learning for few-shot remote sensing image scene classification,
PandRS(191), 2022, pp. 143-154.
Elsevier DOI 2208
Remote sensing image, Few-shot learning, Scene classification, Contrastive learning BibRef

Zhang, P.[Pei], Fan, G.L.[Guo-Liang], Wu, C.[Chanyue], Wang, D.[Dong], Li, Y.[Ying],
Task-Adaptive Embedding Learning with Dynamic Kernel Fusion for Few-Shot Remote Sensing Scene Classification,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Zhao, G.X.[Gui-Xin], Wang, X.S.[Xue-Song], Kong, Y.[Yi], Cheng, Y.[Yuhu],
Spectral-Spatial Joint Classification of Hyperspectral Image Based on Broad Learning System,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Hu, X.P.[Xiao-Pei], Zhao, G.X.[Gui-Xin], Dong, A.[Aimei], Lv, G.H.[Guo-Hua], Zhai, Y.[Yi], Guo, Y.[Ying], Dong, X.J.[Xiang-Jun],
Few-Shot Hyperspectral Image Classification with Spectral-Spatial Feature Fusion Based on Fuzzy Broad Learning System,
ICIP23(3160-3164)
IEEE DOI 2312
BibRef

Kong, Y.[Yi], Wang, X.S.[Xue-Song], Cheng, Y.[Yuhu], Chen, C.L.P.[C. L. Philip],
Hyperspectral Imagery Classification Based on Semi-Supervised Broad Learning System,
RS(10), No. 5, 2018, pp. xx-yy.
DOI Link 1806
BibRef

Huang, W.D.[Wen-Dong], Yuan, Z.W.[Zheng-Wu], Yang, A.X.[Ai-Xia], Tang, C.[Chan], Luo, X.B.[Xiao-Bo],
TAE-Net: Task-Adaptive Embedding Network for Few-Shot Remote Sensing Scene Classification,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Yuan, Z.W.[Zheng-Wu], Huang, W.D.[Wen-Dong], Tang, C.[Chan], Yang, A.[Aixia], Luo, X.B.[Xiao-Bo],
Graph-Based Embedding Smoothing Network for Few-Shot Scene Classification of Remote Sensing Images,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link 2203
BibRef

Wang, J.Y.[Jia-Yan], Wang, X.Q.[Xue-Qin], Xing, L.[Lei], Liu, B.D.[Bao-Di], Li, Z.M.[Zong-Min],
Class-Shared SparsePCA for Few-Shot Remote Sensing Scene Classification,
RS(14), No. 10, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Ma, Y.T.[Yu-Teng], Meng, J.M.[Jun-Min], Liu, B.D.[Bao-Di], Sun, L.[Lina], Zhang, H.[Hao], Ren, P.[Peng],
Dictionary Learning for Few-Shot Remote Sensing Scene Classification,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link 2302
BibRef

Hamzaoui, M.[Manal], Chapel, L.[Laetitia], Pham, M.T.[Minh-Tan], Lefèvre, S.[Sébastien],
Hyperbolic prototypical network for few shot remote sensing scene classification,
PRL(177), 2024, pp. 151-156.
Elsevier DOI 2401
Few-shot learning, Hyperbolic space, Scene classification, Remote sensing BibRef

Dong, Z.[Zhong], Lin, B.[Baojun], Xie, F.[Fang],
Optimizing Few-Shot Remote Sensing Scene Classification Based on an Improved Data Augmentation Approach,
RS(16), No. 3, 2024, pp. 525.
DOI Link 2402
BibRef

Hao, T.[Tao], Zhang, Z.H.[Zhi-Hua], Crabbe, M.J.C.[M. James C.],
Few-Shot Hyperspectral Remote Sensing Image Classification via an Ensemble of Meta-Optimizers with Update Integration,
RS(16), No. 16, 2024, pp. 2988.
DOI Link 2408
BibRef

Liu, B.[Bing], Zhao, H.W.[Hong-Wei], Li, J.[Jiao], Gao, Y.S.[Yan-Sheng], Zhang, J.R.[Jiang-Rong],
SRL-ProtoNet: Self-supervised representation learning for few-shot remote sensing scene classification,
IET-CV(18), No. 7, 2024, pp. 1034-1042.
DOI Link 2411
image classification, natural scenes, remote sensing BibRef

Jia, Y.[Yuyu], Sun, C.C.[Chen-Chen], Gao, J.Y.[Jun-Yu], Wang, Q.[Qi],
Few-shot Remote Sensing Scene Classification via Parameter-free Attention and Region Matching,
PandRS(227), 2025, pp. 265-275.
Elsevier DOI 2508
Remote sensing, Few-shot learning, Region attention BibRef

He, R.K.[Rui-Kun], Zhao, W.[Wenda], Wang, H.P.[Hai-Peng], He, Y.[You],
Cross-Domain Few-Shot Remote Sensing Object Classification via Triplet Relation-Aware Metric,
IP(34), 2025, pp. 6925-6938.
IEEE DOI Code:
WWW Link. 2511
Measurement, Remote sensing, Training, Few shot learning, Semantics, Feature extraction, Benchmark testing, Prototypes, cross-domain few-shot learning BibRef

Zhao, W.[Wenda], Li, Y.X.[Yun-Xiang], Wang, H.P.[Hai-Peng], Lu, H.C.[Hu-Chuan],
First-Order Cross-Domain Meta Learning for Few-Shot Remote Sensing Object Classification,
PAMI(48), No. 6, June 2026, pp. 6365-6379.
IEEE DOI 2605
Remote sensing, Metalearning, Adaptation models, Training, Optimization, Few shot learning, Backpropagation, Training data, learnable affine transformation BibRef

Liu, J.F.[Jian-Feng], Du, Y.[Yibo], Sun, L.[Lifan], Li, X.Z.[Xiao-Zheng], Si, Y.[Yanna], Song, X.L.[Xiao-Li], Zheng, R.[Ruijuan],
GRCD-Net: Guided Global-Local Relational Learning for Few-Shot Fine-Grained and Remote Sensing Scene Classification,
RS(18), No. 10, 2026, pp. 1632.
DOI Link 2605
BibRef

Chen, X.L.[Xi-Liang], Li, L.W.[Long-Wei], Chen, Y.F.[Yu-Feng], Liu, L.[Lei], Wang, Z.Y.[Zhen-Yu], Liu, M.Q.[Ming-Qing], Liu, X.J.[Xiao-Jie], Zhu, G.B.[Guo-Bin],
Few-Shot Remote Sensing Scene Classification via Fusion of Zigzag Scanning Feature Sequence and Riemannian Geometric Barycenter Network,
RS(18), No. 13, 2026, pp. 2264.
DOI Link 2607
BibRef

Zhang, J.J.[Jun-Jie], Rao, Y.T.[Yu-Tao], Huang, X.S.[Xiao-Shui], Li, G.[Guanyi], Zhou, X.[Xin], Zeng, D.[Dan],
Frequency-Aware Multi-Modal Fine-Tuning for Few-Shot Open-Set Remote Sensing Scene Classification,
MultMed(26), 2024, pp. 7823-7837.
IEEE DOI 2405
Task analysis, Prototypes, Training, Visualization, Scene classification, Adaptation models, Semantics, parameter-efficient transfer learning BibRef

Ding, C.[Chen], Yue, J.H.[Jia-Hao], Zheng, S.[Sirui], Dong, Y.Z.[Yi-Zhuo], Hua, W.Q.[Wen-Qiang], Chen, X.L.[Xue-Ling], Xie, Y.[Yu], Yan, S.[Song], Wei, W.[Wei], Zhang, L.[Lei],
Class-Discrepancy Dynamic Weighting for Cross-Domain Few-Shot Hyperspectral Image Classification,
RS(17), No. 15, 2025, pp. 2605.
DOI Link 2508
BibRef

Yang, G.[Gan], Wang, Z.H.[Zhao-Hui],
A Deep Transfer Contrastive Learning Network for Few-Shot Hyperspectral Image Classification,
RS(17), No. 16, 2025, pp. 2800.
DOI Link 2509
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

Zhang, T.Y.[Tian-Yu], Shi, C.P.[Cui-Ping], Liao, D.L.[Di-Ling], Wang, L.G.[Li-Guo],
Deep Spectral Spatial Inverted Residual Network for Hyperspectral Image Classification,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Pan, H.Z.[Hai-Zhu], Zhao, X.Y.[Xiao-Yu], 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
BibRef

Shi, C.P.[Cui-Ping], Sun, J.W.[Jing-Wei], Wang, T.Y.[Tian-Yi], Wang, L.G.[Li-Guo],
Hyperspectral Image Classification Based on a 3D Octave Convolution and 3D Multiscale Spatial Attention Network,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301
BibRef

Ma, B.[Boran], Wang, L.G.[Li-Guo], Wang, H.[Heng],
Hyperspectral Image Classification Based on Two-Branch Multiscale Spatial Spectral Feature Fusion with Self-Attention Mechanisms,
RS(16), No. 11, 2024, pp. 1888.
DOI Link 2406
BibRef

Shi, C.P.[Cui-Ping], Sun, J.W.[Jing-Wei], Wang, L.G.[Li-Guo],
Hyperspectral Image Classification Based on Spectral Multiscale Convolutional Neural Network,
RS(14), No. 8, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Pan, H.Z.[Hai-Zhu], Yan, H.[Hui], Ge, H.[Haimiao], Wang, L.G.[Li-Guo], Shi, C.P.[Cui-Ping],
Pyramid Cascaded Convolutional Neural Network with Graph Convolution for Hyperspectral Image Classification,
RS(16), No. 16, 2024, pp. 2942.
DOI Link 2408
BibRef

Zhang, T.Y.[Tian-Yu], Shi, C.P.[Cui-Ping], Liao, D.L.[Di-Ling], Wang, L.G.[Li-Guo],
A Spectral Spatial Attention Fusion with Deformable Convolutional Residual Network for Hyperspectral Image Classification,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Shi, C.P.[Cui-Ping], Liao, D.L.[Di-Ling], Zhang, T.Y.[Tian-Yu], Wang, L.G.[Li-Guo],
Hyperspectral Image Classification Based on 3D Coordination Attention Mechanism Network,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Pan, H.Z.[Hai-Zhu], Liu, M.[Moqi], Ge, H.[Haimiao], Wang, L.G.[Li-Guo],
One-Shot Dense Network with Polarized Attention for Hyperspectral Image Classification,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Ge, H.M.[Hai-Miao], Wang, L.G.[Li-Guo], Liu, M.[Moqi], Zhu, Y.X.[Yue-Xia], Zhao, X.Y.[Xiao-Yu], Pan, H.Z.[Hai-Zhu], Liu, Y.Z.[Yan-Zhong],
Two-Branch Convolutional Neural Network with Polarized Full Attention for Hyperspectral Image Classification,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link 2302
BibRef

Yang, J.H.[Jing-Hui], Qin, J.[Jia], Qian, J.X.[Jin-Xi], Li, A.[Anqi], Wang, L.G.[Li-Guo],
AL-MRIS: An Active Learning-Based Multipath Residual Involution Siamese Network for Few-Shot Hyperspectral Image Classification,
RS(16), No. 6, 2024, pp. 990.
DOI Link 2403
BibRef

Zhang, Z.Q.[Zhong-Qiang], Gao, D.[Dahua], Liu, D.H.[Dan-Hua], Shi, G.M.[Guang-Ming],
Spectral-Spatial Domain Attention Network for Hyperspectral Image Few-Shot Classification,
RS(16), No. 3, 2024, pp. 592.
DOI Link 2402
BibRef


Cao, M.X.[Meng-Xin], Zhao, G.X.[Gui-Xin], Dong, A.[Aimei], Lv, G.H.[Guo-Hua], Guo, Y.[Ying], Dong, X.J.[Xiang-Jun],
Few-Shot Hyperspectral Image Classification Based on Cross-Domain Spectral Semantic Relation Transformer,
ICIP23(1375-1379)
IEEE DOI 2312
BibRef

Guo, Y.[Ying], He, M.Y.[Ming-Yi], Fan, B.[Bin],
Grid-Transformer for Few-Shot Hyperspectral Image Classification,
ICIP23(755-759)
IEEE DOI 2312
BibRef

Zhong, Q., Chen, L., Qian, Y.,
Few-Shot Learning for Remote Sensing Image Retrieval With MAML,
ICIP20(2446-2450)
IEEE DOI 2011
Image retrieval, Feature extraction, Training, Remote sensing, Task analysis, Data models, Histograms, Remote sensing, MAML BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Hallucination for Few Shot Learning, Augmentation .


Last update:Jul 18, 2026 at 15:29:28