SSHMT: Semi-supervised Hierarchical Merge Tree for Electron Microscopy Image Segmentation

Ting Liu, Miaomiao Zhang, Mehran Javanmardi, Nisha Ramesh, Tolga Tasdizen. SSHMT: Semi-supervised Hierarchical Merge Tree for Electron Microscopy Image Segmentation. In Bastian Leibe, Jiri Matas, Nicu Sebe, Max Welling, editors, Computer Vision - ECCV 2016 - 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part I. Volume 9905 of Lecture Notes in Computer Science, pages 144-159, Springer, 2016. [doi]

@inproceedings{LiuZJRT16,
  title = {SSHMT: Semi-supervised Hierarchical Merge Tree for Electron Microscopy Image Segmentation},
  author = {Ting Liu and Miaomiao Zhang and Mehran Javanmardi and Nisha Ramesh and Tolga Tasdizen},
  year = {2016},
  doi = {10.1007/978-3-319-46448-0_9},
  url = {http://dx.doi.org/10.1007/978-3-319-46448-0_9},
  researchr = {https://researchr.org/publication/LiuZJRT16},
  cites = {0},
  citedby = {0},
  pages = {144-159},
  booktitle = {Computer Vision - ECCV 2016 - 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part I},
  editor = {Bastian Leibe and Jiri Matas and Nicu Sebe and Max Welling},
  volume = {9905},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  isbn = {978-3-319-46447-3},
}