深度学习与遥感论文推荐
期刊论文推荐
1.Yuan, Q., Shen, H., Li, T., Li, Z., Li, S., Jiang, Y., … Zhang, L. (2020). Deep learning in environmental remote sensing: Achievements and challenges. Remote Sensing of Environment, 241, 111716.
2.Cunha, R. L. F. and Silva, B.: ESTIMATING CROP YIELDS WITH REMOTE SENSING AND DEEP LEARNING, (2020), ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-3/W2-2020, 59–64.
3.Mohan, A., Singh, A. K., Kumar, B., & Dwivedi, R. (2020). Review on remote sensing methods for landslide detection using machine and deep learning. Transactions on Emerging Telecommunications Technologies.
4.Yüksel, et al., (2020). Deep Learning for Medicine and Remote Sensing: A Brief Review, International Journal of Environment and Geoinformatics (IJEGEO), 7(3):280-288.
5.Ma, L., Liu, Y., Zhang, X., Ye, Y., Yin, G., & Johnson, B. A. (2019). Deep learning in remote sensing applications: A meta-analysis and review. ISPRS Journal of Photogrammetry and Remote Sensing, 152, 166–177.
6.Paoletti, M. E., Haut, J. M., Plaza, J., & Plaza, A. (2019). Deep learning classifiers for hyperspectral imaging: A review. ISPRS Journal of Photogrammetry and Remote Sensing, 158, 279–317.
7.Audebert, N., Le Saux, B., & Lefevre, S. (2019). Deep Learning for Classification of Hyperspectral Data: A Comparative Review. IEEE Geoscience and Remote Sensing Magazine, 7(2), 159–173.
8.Li, J., Huang, X., & Gong, J. (2019). Deep neural network for remote sensing image interpretation: status and perspectives. National Science Review.
9.Li, S., Song, W., Fang, L., Chen, Y., Ghamisi, P., & Benediktsson, J. A. (2019). Deep Learning for Hyperspectral Image Classification: An Overview. IEEE Transactions on Geoscience and Remote Sensing, 57(9), 6690–6709.
10.Zhu, M., He, Y.N. and He, Q.Y. (2019) A Review of Researches on Deep Learning in Remote Sensing Application. International Journal of Geosciences, 10, 1-11.
11.Mountrakis, G., Li, J., Lu, X., & Hellwich, O. (2018). Deep learning for remotely sensed data. ISPRS Journal of Photogrammetry and Remote Sensing.
12.Aaron E. Maxwell, Timothy A. Warner & Fang Fang (2018) Implementation of machine-learning classification in remote sensing: an applied review, International Journal of Remote Sensing, 39:9, 2784-2817.
13.Li Y, Zhang H, Xue X, Jiang Y, Shen Q. (2018). Deep learning for remote sensing image classification: A survey. WIREs Data Mining Knowl Discov. 2018;8:e1264.
14.Zhu, X. X., Tuia, D., Mou, L., Xia, G.-S., Zhang, L., Xu, F., & Fraundorfer, F. (2017). Deep Learning in Remote Sensing: A Comprehensive Review and List of Resources. IEEE Geoscience and Remote Sensing Magazine, 5(4), 8–36.
15.Cheng, G., Han, J., & Lu, X. (2017). Remote Sensing Image Scene Classification: Benchmark and State of the Art. Proceedings of the IEEE, 105(10), 1865–1883.
16.Audebert, N., Boulch, A., Randrianarivo, H., Le Saux, B., Ferecatu, M., Lefevre, S., & Marlet, R. (2017). Deep learning for urban remote sensing. 2017 Joint Urban Remote Sensing Event (JURSE).
17.Yao, C., Luo, X., Zhao, Y., Zeng, W., & Chen, X. (2017). A review on image classification of remote sensing using deep learning. 2017 3rd IEEE International Conference on Computer and Communications (ICCC).
18.John E. Ball, Derek T. Anderson, Chee Seng Chan, (2017) “Comprehensive survey of deep learning in remote sensing: theories, tools, and challenges for the community,” J. Appl. Remote Sens. 11(4),042609.
19.Zhang, L., Zhang, L., & Du, B. (2016). Deep Learning for Remote Sensing Data: A Technical Tutorial on the State of the Art. IEEE Geoscience and Remote Sensing Magazine, 4(2), 22–40.
20.Zhang, L., Xia, G.-S., Wu, T., Lin, L., & Tai, X. C. (2016). Deep Learning for Remote Sensing Image Understanding. Journal of Sensors, 2016, 1–2.
学位论文推荐
1.张刚.(2020).基于深度学习的遥感图像语义分割关键技术研究[PhD].中国科学院光电技术研究所.
2.王庆.(2019).基于深度学习的遥感影像变化检测方法研究[PhD].武汉大学.
3.张旭东.(2019).基于压缩感知和深度学习的超分辨成像方法研究[PhD].中国科学院上海技术物理研究所.
4.陶翊婷.(2019).基于深度学习的高空间分辨率遥感影像分类方法研究[PhD].武汉大学.
5.朱祺琪.(2018).面向高分辨率遥感影像场景语义理解的概率主题模型研究[PhD].武汉大学.
6.邱康.(2018).基于机器学习的图像超分辨率重建关键技术研究[PhD].武汉大学.
7.吕浩博.(2018).基于深度学习的长时间序列城市制图与变化检测研究[PhD].清华大学.
8.刘娜.(2018).面向遥感图像分类与检索的深度学习特征表达研究[PhD].上海交通大学.
9.胡凡.(2017).基于特征学习的高分辨率遥感图像场景分类研究[PhD].武汉大学.
10.马晓瑞.(2017).基于深度学习的高光谱影像分类方法研究[PhD].大连理工大学.
11.张帆.(2017).面向高分辨率遥感影像分析的深度学习方法研究[PhD].武汉大学.
12.磊风.(2016).面向农业领域的大数据关键技术研究[PhD].中国农业科学院.
MORE
往期精彩
GEE Deep Learning
Google Earth Engine学习资料总结与分享
GEE 综述论文第一篇
GEE 综述论文第二篇
面向科研人员的免费遥感数据集