[6] [6] GU Y, Chanussot J, JIA X, et al. Multiple kernel learning for hyperspectral image classification: a review[J].IEEE Transactions on Geoscience and Remote Sensing, 2017,55(11): 6547-6565.

[7] [7] Aydav P S S, Minz S. Granulation-based self-training for the semi-supervised classification of remote-sensing images[J].Granular Computing, 2020,5(3): 309-327.

[8] [8] CAI W, NING X, ZHOU G, et al. A novel hyperspectral image classification model using bole onvolution with three-directions attention mechanism: small sample and unbalanced learning[J].IEEE Transactions on Geoscience and Remote Sensing, 2022,61: DOI: 10.1109/TGRS.2022.3201056.

[9] [9] HUANG S, ZHANG H, Piurica A. Hybrid-hypergraph regularized multiview subspace clustering for hyperspectral images[J].IEEE Transactions on Geoscience and Remote Sensing, 2021,60(1): 1-16.

[10] [10] ZHONG Z, LI J, LUO Z, et al. Spectral-spatial residual network for hyperspectral image classification: a 3-D deep learning framework[J].IEEE Transactions on Geoscience and Remote Sensing, 2018,56(2): 847-858.

[11] [11] LIU B, YU X, YU A., Deep few-shot learning for hyperspectral image classification[J].IEEE Transactions on Geoscience and Remote Sensing, 2019,57(4): 2290-2304.

[12] [12] SUNG F, YANG Y, ZHANG L. Learning to compare: relation network for few-shot learning[C]//Proceeding of the2018IEEE/CVF Computer Vision and Pattern Recognition Conference, 2018: 1199-1208.

[13] [13] LIU N, LI W, DU Q. Unsupervised feature extraction for hyper-spectral imagery using collaboration-competition graph[J].IEEE Journal of Selected Topics in Signal Processing, 2018,12(6): 1491-1503.

[14] [14] Belkin M, Niyogi P, Sindhwani V. Manifold regularization: a geometric framework for learning from labeled and unlabeled examples[J].Journal of Machine Learning Research,7(24): 2399-2434.

[15] [15] LIU B, YU X, ZHANG P, et al. A semi-supervised convolutional neural network for hyperspectral image classification[J].Remote Sensing Letters, 2017,8(9): 839-848.

[16] [16] MEI S, JI J, GENG Y, et al. Unsupervised spatial-spectral feature learning by 3D convolutional autoencoder for hyperspectral classification[J].IEEE Transactions on Geoscience and Remote Sensing, 2019,57(9): 6808-6820.

[17] [17] MEI S, JI J, HOU J, et al. Learning sensor-specific spatial-spectral features of hyperspectral images via convolutional neural networks[J].IEEE Transactions on Geoscience and Remote Sensing, 2017,55(8): 4520-4533.

[18] [18] LI Z, LIU M, CHEN Y, et al. Deep cross-domain few-shot learning for hyperspectral image classification[J].IEEE Transactions on Geoscience and Remote Sensing, 2021,60(12): 1-18.

[19] [19] SONG J, SHI G, XIE X, et al. Domain-aware stacked autoencoders for zero-shot learning[J].Neurocomputing, 2021,42(9): 118-131.