DW-D³A: dynamic weighted dual-driven domain adaptation for cross-scene hyperspectral image classification

References

• Ahamed, M. H., M. Ali Hossain, and Y. Sarker. 2023. “Dynamic Kernel Network for Hyperspectral Image Classification.” International Journal of Remote Sensing 44 (9): 2847–2866. https://doi.org/10.1080/01431161.2023.2209268.
   Web of Science ®Google Scholar
• Bruzzone, L., M. Chi, and M. Marconcini. 2006. “A Novel Transductive SVM for Semisupervised Classification of Remote-Sensing Images.” IEEE Transactions on Geoscience & Remote Sensing 44 (11–2): 3363–3373. https://doi.org/10.1109/TGRS.2006.877950.
   Web of Science ®Google Scholar
• Debes, C., A. Merentitis, R. Heremans, J. T. Hahn, N. Frangiadakis, T. van Kasteren, W. Liao, et al. 2014. “Hyperspectral and LiDAR Data Fusion: Outcome of the 2013 GRSS Data Fusion Contest.” IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing 7 (6): 2405–2418. https://doi.org/10.1109/JSTARS.2014.2305441.
   Web of Science ®Google Scholar
• Fang, Z., Y. Yang, Z. Li, W. Li, Y. Chen, L. Ma, and Q. Du. 2022. “Confident Learning-Based Domain Adaptation for Hyperspectral Image Classification.” IEEE Transactions on Geoscience & Remote Sensing 60:1–16. https://doi.org/10.1109/TGRS.2022.3166817.
   Google Scholar
• Fan, J., X. Zhang, Y. Chen, and C. Sun. 2023. “Classification of Hyperspectral Image by Preprocessing Method Based Relation Network.” International Journal of Remote Sensing 44 (22): 6929–6953. https://doi.org/10.1080/01431161.2023.2275325.
   Web of Science ®Google Scholar
• Fernando, B., A. Habrard, M. Sebban, and T. Tuytelaars. 2013. “Unsupervised Visual Domain Adaptation Using Subspace Alignment.” IEEE International Conference on Computer Vision, ICCV 2013, Sydney, Australia, December 1-8, 2013, 2960–2967. IEEE Computer Society. https://doi.org/10.1109/ICCV.2013.368.
   Google Scholar
• Fu, J., L. Zhang, B. Zhang, and W. Jia. 2018. “Guided Learning: A New Paradigm for Multi-Task Classification.” Biometric Recognition - 13th Chinese Conference, CCBR 2018, Urumqi, China, August 11-12, 2018, Proceedings, edited by J. Zhou, Y. Wang, Z. Sun, Z. Jia, J. Feng, S. Shan, K. Ubul, and Z. Guo, 239–246. Springer. https://doi.org/10.1007/978-3-319-97909-0_26.
   Google Scholar
• Gao, Q., and S. Lim. 2019. “A Probabilistic Fusion of a Support Vector Machine and a Joint Sparsity Model for Hyperspectral Imagery Classification.” GIScience & Remote Sensing 56 (8): 1129–1147. https://doi.org/10.1080/15481603.2019.1623003.
   Web of Science ®Google Scholar
• Gretton, A., K. M. Borgwardt, M. J. Rasch, B. Schölkopf, and A. J. Smola. 2012. “A Kernel Two-Sample Test.” Journal of Machine Learning Research 13:723–773. https://doi.org/10.5555/2503308.2188410.
   Web of Science ®Google Scholar
• Imani, M., and H. Ghassemian. 2014. “Principal Component Discriminant Analysis for Feature Extraction and Classification of Hyperspectral Images.” 2014 Iranian Conference on Intelligent Systems (ICIS), 1–5. Bam, Iran: IEEE.
   Google Scholar
• Karantzalos, K., C. Karakizi, Z. Kandylakis, and G. Antoniou. 2018. HyRANK Hyperspectral Satellite Dataset I (Version v001). IW III/4.
   Google Scholar
• Kong, Y., X. Wang, Y. Cheng, Y. Chen, and C. L. Philip Chen. 2022. “Graph Domain Adversarial Network with Dual-Weighted Pseudo-Label Loss for Hyperspectral Image Classification.” Geoscience and Remote Sensing Letters, IEEE 19:1–5. https://doi.org/10.1109/LGRS.2021.3135310.
   Google Scholar
• Lasloum, T., H. Alhichri, Y. Bazi, and N. Alajlan. 2021. “SSDAN: Multi-Source Semi-Supervised Domain Adaptation Network for Remote Sensing Scene Classification.” Remote Sensing 13 (19): 3861. https://doi.org/10.3390/rs13193861.
   Web of Science ®Google Scholar
• Le Saux, B., N. Yokoya, R. Hänsch, and S. Prasad. 2018. “2018 IEEE GRSS data fusion contest: Multimodal land use classification [Technical Committees].” IEEE Geoscience and Remote Sensing Magazine 6 (1): 52–54. https://doi.org/10.1109/MGRS.2018.2798161.
   Web of Science ®Google Scholar
• Liu, H., W. Li, X.-G. Xia, M. Zhang, C.-Z. Gao, and R. Tao. 2021. “Spectral Shift Mitigation for Cross-Scene Hyperspectral Imagery Classification.” IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing 14:6624–6638. https://doi.org/10.1109/JSTARS.2021.3091591.
   Google Scholar
• Long, M., Z. Han, W. Jianmin, and I. J. Michael. 2017. “Deep Transfer Learning with Joint Adaptation Networks.” Proceedings of the 34th International Conference on Machine Learning, ICML 2017, Sydney, NSW, Australia, 6-11 August 2017, edited by D. Precup and Y. W. Teh, 2208–2217. PMLR. http://proceedings.mlr.press/v70/long17a.html.
   Google Scholar
• Long, M., J. Wang, G. Ding, J. Sun, and P. S. Yu. 2013. “Transfer Feature Learning with Joint Distribution Adaptation.” IEEE International Conference on Computer Vision, ICCV 2013, Sydney, Australia, December 1-8, 2013, 2200–2207. IEEE Computer Society. https://doi.org/10.1109/ICCV.2013.274.
   Google Scholar
• Matasci, G., M. Volpi, M. F. Kanevski, L. Bruzzone, and D. Tuia. 2015. “Semisupervised Transfer Component Analysis for Domain Adaptation in Remote Sensing Image Classification.” IEEE Transactions on Geoscience & Remote Sensing 53 (7): 3550–3564. https://doi.org/10.1109/TGRS.2014.2377785.
   Web of Science ®Google Scholar
• Pan, S. J., and Q. Yang. 2010. “A Survey on Transfer Learning.” IEEE Transactions on Knowledge and Data Engineering 22 (10): 1345–1359. https://doi.org/10.1109/TKDE.2009.191.
   Web of Science ®Google Scholar
• Saito, K., D. Kim, S. Sclaroff, T. Darrell, and K. Saenko. 2019. “Semi-Supervised Domain Adaptation via Minimax Entropy.” 2019 IEEE/CVF International Conference on Computer Vision, ICCV 2019, Seoul, Korea (South), October 27 - November 2, 2019, 8049–8057. IEEE. https://doi.org/10.1109/ICCV.2019.00814.
   Google Scholar
• Shao, M., D. Kit, and Y. Fu. 2014. “Generalized Transfer Subspace Learning Through Low-Rank Constraint.” International Journal of Computer Vision 109 (1–2): 74–93. https://doi.org/10.1007/S11263-014-0696-6.
   Web of Science ®Google Scholar
• Si, S., D. Tao, and B. Geng. 2010. “Bregman Divergence-Based Regularization for Transfer Subspace Learning.” IEEE Transactions on Knowledge and Data Engineering 22 (7): 929–942. https://doi.org/10.1109/TKDE.2009.126.
   Web of Science ®Google Scholar
• Sun, Z., C. Wang, H. Wang, and J. Li. 2013. “Learn Multiple-Kernel SVMs for Domain Adaptation in Hyperspectral Data.” IEEE Geoscience & Remote Sensing Letters 10 (5): 1224–1228. https://doi.org/10.1109/LGRS.2012.2236818.
   Web of Science ®Google Scholar
• Tuia, D., C. Persello, and L. Bruzzone. 2021. “Recent Advances in Domain Adaptation for the Classification of Remote Sensing Data.” CoRR: abs/2104.07778. https://arxiv.org/abs/2104.07778.
   Google Scholar
• Tzeng, E., J. Hoffman, K. Saenko, and T. Darrell. 2017. “Adversarial Discriminative Domain Adaptation.” 2017 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, Honolulu, HI, USA, July 21-26, 2017, 2962–2971. IEEE Computer Society. https://doi.org/10.1109/CVPR.2017.316.
   Google Scholar
• Wang, H., Y. Cheng, C. L. P. Chen, and X. Wang. 2022. “Hyperspectral Image Classification Based on Domain Adversarial Broad Adaptation Network.” IEEE Transactions on Geoscience & Remote Sensing 60:1–13. https://doi.org/10.1109/TGRS.2021.3128162.
   Web of Science ®Google Scholar
• Wang, H., Y. Cheng, and X. Wang. 2023. “Correlation Subdomain Alignment Network Based Cross-Domain Hyperspectral Image Classification Method.” Journal of Image and Graphics 28 (10): 3255–3266. https://doi.org/10.11834/jig.220763.
   Google Scholar
• Wang, J., Y. Chen, L. Hu, X. Peng, and P. S. Yu. 2018. “Stratified Transfer Learning for Cross-Domain Activity Recognition.” 2018 IEEE International Conference on Pervasive Computing and Communications, PerCom 2018, Athens, Greece, March 19-23, 2018, 1–10. IEEE Computer Society. https://doi.org/10.1109/PERCOM.2018.8444572.
   Google Scholar
• Wang, W., L. Ma, M. Chen, and Q. Du. 2021. “Joint Correlation Alignment-Based Graph Neural Network for Domain Adaptation of Multitemporal Hyperspectral Remote Sensing Images.” IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing 14:3170–3184. https://doi.org/10.1109/JSTARS.2021.3063460.
   Web of Science ®Google Scholar
• Wang, W., Z. Shen, D. Li, P. Zhong, and Y. Chen. 2023. “Probability-Based Graph Embedding Cross-Domain and Class Discriminative Feature Learning for Domain Adaptation.” IEEE Transactions on Image Processing 32:72–87. https://doi.org/10.1109/TIP.2022.3226405.
   Web of Science ®Google Scholar
• Xia, J., N. Yokoya, and A. Iwasaki. 2017. “Ensemble of Transfer Component Analysis for Domain Adaptation in Hyperspectral Remote Sensing Image Classification.” 2017 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017, 4762–4765. Fort Worth, TX, USA. IEEE. https://doi.org/10.1109/IGARSS.2017.8128066.
   Google Scholar
• Xu, Y., X. Fang, J. Wu, X. Li, and D. Zhang. 2016. “Discriminative Transfer Subspace Learning via Low-Rank and Sparse Representation.” IEEE Transactions on Image Processing 25 (2): 850–863. https://doi.org/10.1109/TIP.2015.2510498.
   PubMed Web of Science ®Google Scholar
• Yang, X., Z. Song, I. King, and Z. Xu. 2023. “A Survey on Deep Semi-Supervised Learning.” IEEE Transactions on Knowledge and Data Engineering 35 (9): 8934–8954. https://doi.org/10.1109/TKDE.2022.3220219.
   Web of Science ®Google Scholar
• Yang, J., and X. Yuan. 2013. “Linearized Augmented Lagrangian and Alternating Direction Methods for Nuclear Norm Minimization.” Mathematics of Computation 82 (281): 301–329. https://doi.org/10.1090/S0025-5718-2012-02598-1.
   Web of Science ®Google Scholar
• Yan, K., L. Kou, and D. Zhang. 2018. “Learning Domain-Invariant Subspace Using Domain Features and Independence Maximization.” IEEE Transactions on Cybernetics 48 (1): 288–299. https://doi.org/10.1109/TCYB.2016.2633306.
   PubMed Web of Science ®Google Scholar
• Ye, M., Y. Qian, J. Zhou, and Y. Yan Tang. 2018. “Corrections to “Dictionary Learning-Based Feature-Level Domain Adaptation for Cross-Scene Hyperspectral Image Classification” [Mar 17 1544-1562].” IEEE Transactions on Geoscience & Remote Sensing 56 (5): 3002–3003. https://doi.org/10.1109/TGRS.2018.2789418.
   Web of Science ®Google Scholar
• Zeng, D., S. Zhang, F. Chen, and Y. Wang. 2019. “Multi-Scale CNN Based Garbage Detection of Airborne Hyperspectral Data.” Institute of Electrical and Electronics Engineers Access 7:104514–104527. https://doi.org/10.1109/ACCESS.2019.2932117.
   Google Scholar
• Zhang, Y., W. Li, W. Sun, R. Tao, and Q. Du. 2023. “Single-Source Domain Expansion Network for Cross-Scene Hyperspectral Image Classification.” IEEE Transactions on Image Processing 32:1498–1512. https://doi.org/10.1109/TIP.2023.3243853.
   Web of Science ®Google Scholar
• Zhang, Y., W. Li, R. Tao, J. Peng, Q. Du, and Z. Cai. 2021. “Cross-Scene Hyperspectral Image Classification with Discriminative Cooperative Alignment.” IEEE Transactions on Geoscience & Remote Sensing 59 (11): 9646–9660. https://doi.org/10.1109/TGRS.2020.3046756.
   Web of Science ®Google Scholar
• Zhang, Y., W. Li, M. Zhang, Y. Qu, R. Tao, and H. Qi. 2023. “Topological Structure and Semantic Information Transfer Network for Cross-Scene Hyperspectral Image Classification.” IEEE Transactions on Neural Networks and Learning Systems 34 (6): 2817–2830. https://doi.org/10.1109/TNNLS.2021.3109872.
   PubMed Web of Science ®Google Scholar
• Zhang, X., J. Yan, J. Tian, W. Li, X. Gu, and Q. Tian. 2023. “Objective Evaluation-Based Efficient Learning Framework for Hyperspectral Image Classification.” GIScience & Remote Sensing 60 (1): 2225273. https://doi.org/10.1080/15481603.2023.2225273.
   Web of Science ®Google Scholar
• Zhang, L., W. Zuo, and D. Zhang. 2016. “LSDT: Latent Sparse Domain Transfer Learning for Visual Adaptation.” IEEE Transactions on Image Processing 25 (3): 1177–1191. https://doi.org/10.1109/TIP.2016.2516952.
   PubMed Web of Science ®Google Scholar
• Zhou, S., H. Wu, and Z. Xue. 2022. “Grouped Subspace Linear Semantic Alignment for Hyperspectral Image Transfer Learning.” IEEE Transactions on Geoscience & Remote Sensing 60:1–16. https://doi.org/10.1109/TGRS.2022.3184691.
   Web of Science ®Google Scholar
• Zhu, Y., F. Zhuang, J. Wang, G. Ke, J. Chen, J. Bian, H. Xiong, and Q. He. 2021. “Deep Subdomain Adaptation Network for Image Classification.” IEEE Transactions on Neural Networks and Learning Systems 32 (4): 1713–1722. https://doi.org/10.1109/TNNLS.2020.2988928.
   PubMed Web of Science ®Google Scholar
• Zu, B., H. Wang, J. Li, Z. He, Y. Li, and Z. Yin. 2023. “Weighted Residual Self-Attention Graph-Based Transformer for Spectral–Spatial Hyperspectral Image Classification.” International Journal of Remote Sensing 44 (3): 852–877. https://doi.org/10.1080/01431161.2023.2171744.
   Web of Science ®Google Scholar