[1] Zhang B. Hyperspectral data mining supported by temporal and spatial information[D](2002).

[2] Yuan Y H, Lin Z Y. Overview of hyperspectral remote sensing technology[J]. China Water Transport, 155-157(2007).

[3] Lacar F M, Lewis M M, Grierson I T. Use of hyperspectral imagery for mapping grape varieties in the Barossa Valley, South Australia[C], 2875-2877(2001).

[4] Chen P F. Applications and trends of unmanned aerial vehicle in agriculture[J]. Journal of Zhejiang University (Agriculture and Life Sciences), 44, 399-406(2018).

[5] van der Meer F. Analysis of spectral absorption features in hyperspectral imagery[J]. International Journal of Applied Earth Observation and Geoinformation, 5, 55-68(2004).

[6] Stuffler T, Förster K, Hofer S et al. Hyperspectral imaging: an advanced instrument concept for the EnMAP mission (Environmental Mapping and Analysis Programme)[J]. Acta Astronautica, 65, 1107-1112(2009).

[7] Plaza A, Du Q, Chang Y L et al. High performance computing for hyperspectral remote sensing[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 4, 528-544(2011).

[8] Hu W, Huang Y Y, Wei L et al. Deep convolutional neural networks for hyperspectral image classification[J]. Journal of Sensors, 2015, 258619(2015).

[9] Makantasis K, Karantzalos K, Doulamis A et al. Deep supervised learning for hyperspectral data classification through convolutional neural networks[C], 4959-4962(2015).

[10] Lee H, Kwon H. Going deeper with contextual CNN for hyperspectral image classification[J]. IEEE Transactions on Image Processing, 26, 4843-4855(2017).

[11] Chen H, Deng F. Hyperspectral remote sensing image classification based on decomposed three-dimensional convolutional neural network[J]. Science of Surveying and Mapping, 45, 96-102, 129(2020).

[12] Chen Y S, Jiang H L, Li C Y et al. Deep feature extraction and classification of hyperspectral images based on convolutional neural networks[J]. IEEE Transactions on Geoscience and Remote Sensing, 54, 6232-6251(2016).

[13] Liu J M, Zheng C, Zhang L M et al. Hyperspectral image classification method based on image reconstruction feature fusion[J]. Chinese Journal of Lasers, 48, 0910001(2021).

[14] Zhang X D, Wang T J, Zhu S J et al. Hyperspectral image classification based on dilated convolutional attention neural network[J]. Acta Optica Sinica, 41, 0310001(2021).

[15] Yan M J, Su X Y. Hyperspectral image classification based on three-dimensional dilated convolutional residual neural network[J]. Acta Optica Sinica, 40, 1628002(2020).

[16] Zhong Y F, Hu X, Luo C et al. WHU-Hi: UAV-borne hyperspectral with high spatial resolution (H2) benchmark datasets and classifier for precise crop identification based on deep convolutional neural network with CRF[J]. Remote Sensing of Environment, 250, 112012(2020).

[17] Zhong Z L, Li J, Luo Z M et al. Spectral-spatial residual network for hyperspectral image classification: a 3-D deep learning framework[J]. IEEE Transactions on Geoscience and Remote Sensing, 56, 847-858(2018).

[18] Wei X P, Yu X C, Tan X et al. Hyperspectral image classification based on residual dense network[J]. Laser & Optoelectronics Progress, 56, 151006(2019).

[19] Gao H M, Yang Y, Li C M et al. Multiscale residual network with mixed depthwise convolution for hyperspectral image classification[J]. IEEE Transactions on Geoscience and Remote Sensing, 59, 3396-3408(2021).

[20] Zhang W. Research on hyperspectral image classification based on lightweight neural network[D](2021).

[21] Roy S K, Krishna G, Dubey S R et al. HybridSN: exploring 3-D-2-D CNN feature hierarchy for hyperspectral image classification[J]. IEEE Geoscience and Remote Sensing Letters, 17, 277-281(2020).

[22] Gong H, Li Q X, Li C L et al. Multiscale information fusion for hyperspectral image classification based on hybrid 2D-3D CNN[J]. Remote Sensing, 13, 2268(2021).

[23] Feng F, Wang S T, Zhang J et al. Hyperspectral images classification based on multi-feature fusion and hybrid convolutional neural networks[J]. Laser & Optoelectronics Progress, 58, 0810010(2021).

[24] Liu J X, Ban W, Chen Y et al. Multi-dimensional CNN fused algorithm for hyperspectral remote sensing image classification[J]. Chinese Journal of Lasers, 48, 1610003(2021).

[25] Zhong Y F, Wang X Y, Xu Y et al. Mini-UAV-borne hyperspectral remote sensing: from observation and processing to applications[J]. IEEE Geoscience and Remote Sensing Magazine, 6, 46-62(2018).

[26] Zhao H S, Shi J P, Qi X J et al. Pyramid scene parsing network[EB/OL]. https://arxiv.org/abs/1612.01105

[27] Howard A G, Zhu M L, Chen B et al. MobileNets: efficient convolutional neural networks for mobile vision applications[EB/OL]. https://arxiv.org/abs/1704.04861

[28] Lin M, Chen Q, Yan S C. Network In network[EB/OL]. https://arxiv.org/abs/1312.4400

[29] Szegedy C, Liu W, Jia Y Q et al. Going deeper with convolutions[C](2015).