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Research Letter

Hyperspectral image classification using a deep relation network with random replacement data augmentation

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Pages 805-815 | Received 22 Jan 2024, Accepted 06 Jul 2024, Published online: 27 Jul 2024

References

  • Audebert, N., B. L. Saux, and S. Lefevre. 2019. “Deep Learning for Classification of Hyperspectral Data: A Comparative Review.” IEEE Geoscience and Remote Sensing Magazine 7 (2): 159–173. https://doi.org/10.1109/MGRS.2019.2912563.
  • Bioucas, J. M., A. Plaza, G. Camps-Valls, P. Scheunders, N. M. Nasrabadi, and J. Chanussot. 2013. “Hyperspectral Remote Sensing Data Analysis and Future Challenges.” IEEE Geoscience and Remote Sensing Magazine 1 (2): 6–36. https://doi.org/10.1109/MGRS.2013.2244672.
  • Deng, B., S. Jia, and D. Shi. 2020. “Deep Metric Learning-Based Feature Embedding for Hyperspectral Image Classification.” IEEE Transactions on Geoscience & Remote Sensing 58 (2): 1422–1435. https://doi.org/10.1109/TGRS.2019.2946318.
  • Ghamisi, P. 2017. “Advances in Hyperspectral Image and Signal Processing: A Comprehensive Overview of the State of the Art.” IEEE Geoscience and Remote Sensing Magazine 5 (4): 37–78. https://doi.org/10.1109/MGRS.2017.2762087.
  • Green, R. O. 1998. “Imaging Spectroscopy and the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS).” Remote Sensing of Environment 65 (3): 227–248. https://doi.org/10.1016/S0034-4257(98)00064-9.
  • Haut, J. M., M. E. Paoletti, J. Li, A. Plaza, and J. Plaza. 2019. “Hyperspectral Image Classification Using Random Occlusion Data Augmentation.” IEEE Geoscience & Remote Sensing Letters 16 (11): 1751–1755. https://doi.org/10.1109/LGRS.2019.2909495.
  • Jia, S., S. Jiang, Z. Lin, N. Li, M. Xu, and S. Yu. 2021. “A Survey: Deep Learning for Hyperspectral Image Classification with Few Labeled Sample.” Neurocomputing 448:179–204. https://doi.org/10.1016/j.neucom.2021.03.035.
  • Li, W., G. Wu, F. Zhang, and Q. Du. 2017. “Hyperspectral Image Classification Using Deep Pixel-Pair Features.” IEEE Transactions on Geoscience & Remote Sensing 55 (2): 844–853. https://doi.org/10.1109/TGRS.2016.2616355.
  • Li, Y., H. Zhang, and Q. S. Kweon. 2017. “Spectral–Spatial Classification of Hyperspectral Imagery with 3D Convolutional Neural Network.” Remote Sensing 9 (1): 67. https://doi.org/10.3390/rs9010067.
  • Lin, M., Q. Chen, and S. Yan. 2013. “Network in Network.” arXiv 1312:4400. https://doi.org/10.48550/arXiv.1312.4400.
  • Snell, J., K. Swersky, and R. Zemel. 2017. “Prototypical Networks for Few-Shot Learning.” In 31st Conference on Neural Information Processing Systems, Long Beach, CA, USA, 4077–4087.
  • Sun, Q., X. Liu, and M. Fu. 2017. “Classification of Hyperspectral Image Based on Principal Component Analysis and Deep Learning.” In 2017 7th IEEE International Conference on Electronics Information and Emergency Communication (ICEIEC), Macau, China, 356–359.
  • Wang, W., Y. Chen, X. He, and Z. Li. 2022. “Soft Augmentation-Based Siamese CNN for Hyperspectral Image Classification with Limited Training Samples.” IEEE Geoscience & Remote Sensing Letters 19 (2): 1–5. https://doi.org/10.1109/LGRS.2021.3103180.
  • Weinberger, K. Q., and L. K. Saul. 2009. “Distance Metric Learning for Large Margin Nearest Neighbor Classification.” Journal of Machine Learning Research 10:207–244. https://doi.org/10.5555/1577069.1577078.
  • Woo, S., J. Park, J. Lee, and I. S. Kweon. 2018. “CBAM: Convolutional Block Attention Module.” In Computer Vision – ECCV 2018, Munich, Germany, 3–19. Vol. 11. https://doi.org/10.1007/978-3-030-01234-2_1.
  • Yang, F. S. Y., L. Zhang, T. Xiang, P. H. Torr, and T. M. Hospedales. 2018. “Learning to Compare: Relation Network for Few-Shot Learning.“ In 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA, 1199–1208. https://doi.org/10.1109/CVPR.2018.00131.
  • Yu, S., S. Jia, and C. Xu. 2017. “Convolutional Neural Networks for Hyperspectral Image Classification.” Neurocomputing 219:88–98. https://doi.org/10.1016/j.neucom.2016.09.010.

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