Evaluating the quality of binary partition trees based on uncertain semantic ground-truth for image segmentation. Randrianasoa, J. F., Kurtz, C., Gançarski, P., Desjardin, E., & Passat, N. In 2017 IEEE International Conference on Image Processing, ICIP 2017, Beijing, China, September 17-20, 2017, pages 3874–3878, 2017. IEEE.
Evaluating the quality of binary partition trees based on uncertain semantic ground-truth for image segmentation [link]Paper  doi  bibtex   
@inproceedings{DBLP:conf/icip/RandrianasoaKGD17,
  author    = {Jimmy Francky Randrianasoa and
               Camille Kurtz and
               Pierre Gan{\c{c}}arski and
               Eric Desjardin and
               Nicolas Passat},
  title     = {Evaluating the quality of binary partition trees based on uncertain
               semantic ground-truth for image segmentation},
  booktitle = {2017 {IEEE} International Conference on Image Processing, {ICIP} 2017,
               Beijing, China, September 17-20, 2017},
  pages     = {3874--3878},
  publisher = {{IEEE}},
  year      = {2017},
  url       = {https://doi.org/10.1109/ICIP.2017.8297008},
  doi       = {10.1109/ICIP.2017.8297008},
  timestamp = {Tue, 29 Dec 2020 00:00:00 +0100},
  biburl    = {https://dblp.org/rec/conf/icip/RandrianasoaKGD17.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

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