The growing hierarchical self-organizing map: exploratory analysis of high-dimensional data

By Andreas Rauber, Dieter Merkl, Michael Dittenbach. 2002

466 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. J. Urgen Schmidhuber
2. David R Ha
3. Alex Graves
4. Sergey Levine
5. Yoshua Bengio
6. Quoc V. Le
7. Faustino J. Gomez
8. Mohit Bansal

In Computer Vision and Pattern Recognition

1. J. Urgen Schmidhuber
2. Luc Van Gool
3. Xiaogang Wang
4. Andrew Zisserman
5. Trevor Darrell
6. Ming-Hsuan Yang
7. Dacheng Tao
8. Alan L. Yuille

Citations in the corpus

• Deep learning in neural networks: An overview (2014, background): “3) self-organizing Kohonen maps (e.g., Koikkalainen and Oja, 1990; Lampinen and Oja, 1992; Versino and Gambardella, 1996; Dittenbach et al., 2000; Rauber et al., 2002), hierarchical Gaussian potential function networks (Lee and Kil, 1991), layer-wise UL of feature hierarchies fed into SL classifiers”