Master-slave hierarchy local information driven fuzzy C-means clustering for noisy image segmentation
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Software
Link
https://link.springer.com/content/pdf/10.1007/s00371-023-02821-1.pdf
Reference64 articles.
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2. Nida, M.Z., Musbah, J.A.: Survey on image segmentation techniques. Procedia Comput. Sci. 62, 797–806 (2015). https://doi.org/10.1016/j.procs.2015.09.027
3. Shi, J., Malik, J.: Normalized cuts and image segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 22(8), 888–905 (2000). https://doi.org/10.1109/34.868688
4. Goyal, S., Kumar, S., Zaveri, M.A., Shukla, A.K.: Fuzzy similarity measure based spectral clustering framework for noisy image segmentation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 25(4), 649–673 (2017). https://doi.org/10.1142/S0218488517500283
5. Gao, X., Zhang, Y., Wang, H., et al.: A modified fuzzy clustering algorithm based on dynamic relatedness model for image segmentation. Vis. Comput. (2022). https://doi.org/10.1007/s00371-022-02430-4
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