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docs: add papers using cc3d section
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README.md

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@@ -291,6 +291,12 @@ Fig. 6: Mask for the 6-way problem with phantom labels P, Q, and R added.
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You can even use multiple routes to propagate information if a label is missing. For example, if path (a,P,b) is unavailable due to a missing P, you could potentially transmit information using path (a,R,c,Q,b).
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## Papers Using cc3d
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A number of papers are using cc3d now. Many of them seem to be deep learning applications as instance segmentation is liable to generate touching non-binary labels. Some are in geoscience, neuroscience, and medical fields. If cc3d is helpful to you, please feel free to [email us](https://github.com/william-silversmith/) and let us know. We might be able to offer some tips if its performance critical (though we can't guarantee timeliness of response). There're so many variations of the CCL problem, you might be surprised at what you can do.
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https://scholar.google.com/scholar?as_ylo=2019&q=connected-components-3d&hl=en&as_sdt=0,31
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## References
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1. A. Rosenfeld and J. Pfaltz. "Sequential Operations in Digital Picture Processing". Journal of the ACM. Vol. 13, Issue 4, Oct. 1966, Pg. 471-494. doi: 10.1145/321356.321357 ([link](https://dl.acm.org/citation.cfm?id=321357))

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