Sea ice image classification based on ResFPG network and heterogeneous data fusion

References

• Bobylev, L. P., and M. W. Miles. 2020. “Sea Ice in the Arctic Paleoenvironments.” Sea Ice in the Arctic 9–56. doi:10.1007/978-3-030-21301-5_2.
   Google Scholar
• Chen, Y. S., X. Zhao, and X. P. Jia. 2015. “Spectral–Spatial Classification of Hyperspectral Data Based on Deep Belief Network.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 8 (6): 2381–2392. doi:10.1109/JSTARS.2015.2388577.
   Web of Science ®Google Scholar
• Cui, Y. R., B. Zou, Z. Han, L. J. Shi, and S. Liu. 2019. “Feasibility Analysis of Application of Convolutional Neural Network in SAR Remote Sensing Sea Ice Classification.” Marine Forecasts 36 (5): 77–85.
   Google Scholar
• Dowden, B., O. D. Silva, W. Huang, and O. Dan. 2020. “Sea Ice Classification via Deep Neural Network Semantic Segmentation.” IEEE Sensor Journal 21 (10): 11879–11888. doi:10.1109/JSEN.2020.3031475.
   Web of Science ®Google Scholar
• Gao, Y. H., F. Gao, J. Y. Dong, and S. K. Wang. 2019. “Transferred Deep Learning for Sea Ice Change Detection from Synthetic-Aperture Radar Images.” IEEE Geoscience and Remote Sensing Letters 16 (10): 1655–1659. doi:10.1109/LGRS.2019.2906279.
   Web of Science ®Google Scholar
• Giuseppe, S., G. Massimiliano, M. Antonio, and G. Raffaele. 2018. “A CNN-Based Fusion Method for Feature Extraction from Sentinel Data.” Remote Sensing 10 (2): 236. doi:10.3390/rs10020236.
   Web of Science ®Google Scholar
• Han, Y. L., Y. Gao, Y. Zhang, J. Wang, and S. H. Yang. 2019. “Hyperspectral Sea Ice Image Classification Based on the Spectral-Spatial-Joint Feature with Deep Learning.” Remote Sensing 11 (18): 2170. doi:10.3390/rs11182170.
   Web of Science ®Google Scholar
• He, K., X. Zhang, S. Ren, and J. Sun. 2015. “Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition.” IEEE Transactions on Pattern Analysis and Machine Intelligence 37 (9): 1904–1916. doi:10.1007/978-3-319-10578-9_23.
   PubMed Web of Science ®Google Scholar
• He, K., X. Zhang, S. Ren, and J. Sun. 2016. “Deep Residual Learning for Image Recognition” 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2016: 770–778. doi:10.1109/CVPR.2016.90.
   Google Scholar
• Hong, D., L. Gao, N. Yokoya, J. Yao, J. Chanussot, Q. Du, and B. Zhang. 2021. “More Diverse Means Better: Multimodal Deep Learning Meets Remote-Sensing Imagery Classification.” I EEE Transactions on Geoscience and Remote Sensing 59 (5): 4340–4354. doi:10.1109/TGRS.2020.3016820.
   Web of Science ®Google Scholar
• J, L., A. P. Doulgeris, and W. Dierking. 2021. “An Optimal Decision-Tree Design Strategy and Its Application to Sea Ice Classification from SAR Imagery.” Remote Sensing 11 (13): 1574. doi:10.3390/rs11131574.
   Web of Science ®Google Scholar
• Khaleghian, S., H. Ullah, T. Krmer, N. Hughes, and A. Marinoni. 2021. “Sea Ice Classification of SAR Imagery Based on Convolution Neural Networks.” Remote Sensing 13 (9): 1734. doi:10.3390/rs13091734.
   Web of Science ®Google Scholar
• Kim, J., J. Koh, Y. Kim, J. Choi, Y. Hwang, and J. W. Choi. 2018. Robust Deep Multi-Modal Learning Based on Gated Information Fusion Network. Springer. doi:10.1007/978-3-030-20870-7_6.
   Google Scholar
• Kruk, R., M. C. Fuller, A. S. Komarov, D. Isleifson, and I. Jeffrey. 2020. “Proof of Concept for Sea Ice Stage of Development Classification Using Deep Learning.” Remote Sensing 12 (15): 2486. doi:10.3390/rs12152486.
   Web of Science ®Google Scholar
• Lapini, A., G. Fontanelli, S. Pettinato, E. Santi, S. Paloscia, D. Tapete, and F. Cigna. 2020. “Application of Deep Learning to Optical and SAR Images for the Classification of Agricultural Areas in Italy.” IEEE International Geoscience and Remote Sensing Symposium 2020: 4163–4166. doi:10.1109/IGARSS39084.2020.9323190.
   Google Scholar
• Lin, T. Y., P. Dollar, R. Girshick, K. He, B. Hariharan, and S. Belongie. 2017. “Feature Pyramid Networks for Object Detection.” 017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017: 936–944. doi:10.1109/CVPR.2017.106.
   Google Scholar
• Ren, Y., H. Xu, B. Liu, and X. Li. 2020. “Sea Ice and Open Water Classification of SAR Images Using a Deep Learning Model.” IEEE International Geoscience and Remote Sensing Symposium 2020: 3051–3054. doi:10.1109/IGARSS39084.2020.9323990.
   Google Scholar
• Song, W., M. H. Li, Q. He, D. M. Huang, C. Perra, and A. Liotta. 2018. “A Residual Convolution Neural Network for Sea Ice Classification with Sentinel-1 SAR Imagery.” 2018 IEEE International Conference on Data Mining Workshops (ICDMW): 795–802. doi:10.1109/ICDMW.2018.00119.
   Google Scholar
• Wang, L., K. A. Scott, L. Lin, and D. A. Clausi. 2016. “Sea Ice Concentration Estimation During Melt from Dual-Pol SAR Scenes Using Deep Convolutional Neural Networks: A Case Study.” IEEE Transaction on Geoscience and Remote Sensing 54 (8): 4524–4533. doi:10.1109/TGRS.2016.2543660.
   Web of Science ®Google Scholar
• Wang, Z. Y., P. L. Sun, L. H. Wang, M. Y. Zhang, and Z. H. Wang. 2021. “Monitoring Sea Ice in Liaodong Bay of Bohai Sea During the Freezing Period of 2017/2018 Using Sentinel-2 Remote Sensing Data.” Journal of Spectroscopy 16. doi:10.1155/2021/9974845.
   Web of Science ®Google Scholar
• Xu, X. D., W. Li, Q. Ran, Q. Du, L. R. Gao, and B. Zhang. 2018. “Multisource Remote Sensing Data Classification Based on Convolutional Neural Network.” IEEE Transactions on Geoscience and Remote Sensing 56 (2): 937–949. doi:10.1109/TGRS.2017.2756851.
   Web of Science ®Google Scholar
• Zakhvatkina, N., V. G. Smirnov, and I. Bychkova. 2019. “Satellite SAR Data-Based Sea Ice Classification: An Overview.” Geosciences 9 (4): 152. doi:10.3390/geosciences9040152.
   Web of Science ®Google Scholar