32篇深度学习与遥感论文推荐

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.