Multineuronal vectorization is more efficient than time-segmental vectorization for information extraction from neuronal activities in the inferior temporal cortex

Hidekazu Kaneko, Hiroshi Tamura, Shunta Tate, Takahiro Kawashima, Shinya S. Suzuki, Ichiro Fujita. Multineuronal vectorization is more efficient than time-segmental vectorization for information extraction from neuronal activities in the inferior temporal cortex. Neural Networks, 23(6):733-742, 2010. [doi]

@article{KanekoTTKSF10,
  title = {Multineuronal vectorization is more efficient than time-segmental vectorization for information extraction from neuronal activities in the inferior temporal cortex},
  author = {Hidekazu Kaneko and Hiroshi Tamura and Shunta Tate and Takahiro Kawashima and Shinya S. Suzuki and Ichiro Fujita},
  year = {2010},
  doi = {10.1016/j.neunet.2010.03.002},
  url = {http://dx.doi.org/10.1016/j.neunet.2010.03.002},
  researchr = {https://researchr.org/publication/KanekoTTKSF10},
  cites = {0},
  citedby = {0},
  journal = {Neural Networks},
  volume = {23},
  number = {6},
  pages = {733-742},
}