jcorso.regions.bib

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@article{ChCoPR2017,
  author = {Chen, C. and {\bf Corso}, {\bf J. J.}},
  journal = {Pattern Recognition},
  pages = {15--28},
  tags = {image understanding, segmentation, computer vision},
  title = {Joint occlusion boundary detection and figure/ground assignment by extracting common-fate fragments in a back-projection scheme},
  volume = {64},
  year = {2017}
}
@article{CoHaCVIU2009,
  author = {{\bf Corso},{\bf J. J.} and Hager, G. D.},
  journal = {{Computer Vision and Image Understanding}},
  pages = {446--458},
  tags = {computer vision, feature extraction, image retrieval},
  title = {{Image Description with Features that Summarize}},
  url = {http://web.eecs.umich.edu/~jjcorso/pubs/cviu2009_regions.pdf},
  volume = {113},
  year = {2009}
}
@inproceedings{CoHaCVPR05,
  author = {{\bf Corso},{\bf J. J.} and Hager, G. D.},
  booktitle = {{Proceedings of IEEE Conference on Computer Vision and Pattern Recognition}},
  pages = {184--190},
  tags = {computer vision, feature extraction, image retrieval, segmentation},
  title = {{Coherent Regions for Concise and Stable Image Description }},
  url = {http://web.eecs.umich.edu/~jjcorso/pubs/jcorso_cvpr2005.pdf},
  volume = {2},
  year = {2005}
}
@inproceedings{CoHaICPR04,
  author = {{\bf Corso},{\bf J. J.} and Dewan, M. and Hager, G. D.},
  booktitle = {{Proceedings of 17th International Conference on Pattern Recogntion (ICPR 2004)}},
  tags = {computer vision, segmentation, graph cuts, fusion},
  title = {{Image Segmentation Through Energy Minimization Based Subspace Fusion}},
  url = {http://web.eecs.umich.edu/~jjcorso/pubs/jcorso_ICPR2004.pdf},
  year = {2004}
}
@techreport{CoHaCIRL2004,
  author = {{\bf Corso},{\bf J. J.} and Dewan, M. and Hager, G. D.},
  institution = {The Johns Hopkins University},
  number = {~CIRL-TR-04-01},
  tags = {computer vision, segmentation, graph cuts, fusion},
  title = {{Image Segmentation Through Energy Minimization Based Subspace Fusion}},
  url = {http://web.eecs.umich.edu/~jjcorso/pubs/corso_tr0401.pdf},
  year = {2004}
}