Markovian Segmentation of Non-stationary Data Corrupted by Non-stationary Noise
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-12097-8_3
Reference12 articles.
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2. Benboudjema, D., Pieczynski, W.: Unsupervised statistical segmentation of nonstationary images using triplet Markov fields. Pattern Anal. Mach. Intell. IEEE Trans. 29(8), 1367–1378 (2007)
3. Boudaren, M.E.Y., Pieczynski, W., Monfrini, E.: Unsupervised segmentation of non stationary data hidden with non stationary noise. In: International Workshop on Systems, Signal Processing and their Applications, WOSSPA, pp. 255–258 (2011)
4. Chen, M., Cho, J., Zhao, H.: Incorporating biological pathways via a Markov random field model in genome-wide association studies. PLoS Genetics 7(4), e1001353 (2011). https://doi.org/10.1371/journal.pgen.1001353
5. Deng, H., Clausi, D.: Unsupervised segmentation of synthetic aperture radar sea ice imagery using a novel Markov random field model. IEEE Trans. Geosci. Remote Sens. 43(3), 528–538 (2005). https://doi.org/10.1109/tgrs.2004.839589
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