Multi-layered GMDH-type neural network self-selecting optimum neural network architecture and its application to 3-dimensional medical image recognition of blood vessels

By T. Kondo, J. Ueno. 2008

45 citations recorded by the source corpus.

How researchers see this paper

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

1. Jianmin Jiang
2. Jinchang Ren
3. Paul R. Trundle
4. J. Urgen Schmidhuber
5. David R Ha
6. Yoshua Bengio
7. Sergey Levine
8. Quoc V. Le

Citations in the corpus

• Deep learning in neural networks: An overview (2014, methodology): “ere have been numerous applications of GMDH-style nets, e.g. (Ikeda et al., 1976; Farlow, 1984; Madala and Ivakhnenko, 1994; Ivakhnenko, 1995; Kondo, 1998; Kord´ık et al., 2003; Witczak et al., 2006; Kondo and Ueno, 2008). 5.4 1979: Convolution + Weight Replication + Subsampling (Neocognitron) Apart”
• Medical image analysis with artificial neural networks (2010, methodology): “In [54] Kondo and Ueno applied a GMDH neural network to blood vessel image recognition, with automatic selection of an architecture from three distinct network types, further demonstrating the suitability of this approach for medical imaging.”