Ship Recognition Based on Active Learning and Composite Kernel SVM-Reference-Cited by-同舟云学术

Ship Recognition Based on Active Learning and Composite Kernel SVM

Published:2015 Issue: Volume: Page:198-207
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
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Author:

Pan Bin,Jiang Zhiguo,Wu Junfeng,Zhang Haopeng,Luo Penghao

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-662-47791-5_23

Reference20 articles.

1. Du, C., Sun, J., Li, Z., Teng, S.: Method for Ship Recognition Using Optical Remote Sensing Data. Journal of Image and Graphics 17(4), 589–595 (2012)

2. Lan, J., Wan, L.: Automatic Ship Target Classification Based on Aerial Images. Proceedings of SPIE 7156(12), 1–10 (2009). Bellingham Wash

3. Uma Selvi, M., Suresh Kumar, S.: A Novel Approach for Ship Recognition Using Shape and Texture. International Journal of Advanced Information Technology 1(5), 23–29 (2011)

4. Guo, W., Xia, X., Xiaofei, W.: A Remote Sensing Ship Recognition Method Based on Dynamic Probability Generative Model. Expert Systems with Applications 41(14), 6446–6458 (2014)

5. Tuia, D., Volpi, M., Copa, L., Kanevski, M., Muñoz-Mar, J.: A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification. IEEE Journal of Selected Topics in Signal Processing 5(3), 606–617 (2011)

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