Hyperspectral image segmentation through evolved cellular automata

Author:

Priego Blanca,Souto Daniel,Bellas Francisco,Duro Richard J.

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference36 articles.

1. Statistics of real-world hyperspectral images;Chakrabarti;Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2011

2. Chang, C., Lin, C., 2008. LIBSVM – a library for support vector machines. http://www.csie.ntu.edu.tw/%E2%88%BCcjlin/libsvm.

3. Chuanwu, Z., 2008. Performance analysis of the CPLD/FPGA implementation of cellular automata. In: IEEE Transaction of the 2008 International Conference on Embedded Software and Systems Symposia (ICESS2008), pp. 308–311.

4. Image segmentation for the purpose of object-based classification;Darwish;Proceedings 2003 Geoscience and Remote Sensing Symposium,2003

5. Spectroscopic imaging and chemometrics: a powerful combination for global and local sample analysis;De Juan;TrAC Trends Anal. Chem.,2004

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