LoGID: An adaptive framework combining local and global incremental learning for dynamic selection of ensembles of HMMs

Paulo Rodrigo Cavalin, Robert Sabourin, Ching Y. Suen. LoGID: An adaptive framework combining local and global incremental learning for dynamic selection of ensembles of HMMs. Pattern Recognition, 45(9):3544-3556, 2012. [doi]

@article{CavalinSS12,
  title = {LoGID: An adaptive framework combining local and global incremental learning for dynamic selection of ensembles of HMMs},
  author = {Paulo Rodrigo Cavalin and Robert Sabourin and Ching Y. Suen},
  year = {2012},
  doi = {10.1016/j.patcog.2012.02.034},
  url = {http://dx.doi.org/10.1016/j.patcog.2012.02.034},
  researchr = {https://researchr.org/publication/CavalinSS12},
  cites = {0},
  citedby = {0},
  journal = {Pattern Recognition},
  volume = {45},
  number = {9},
  pages = {3544-3556},
}