Artificial vision by multi-layered neural networks: Neocognitron and its advances

By Kunihiko Fukushima. 2013

104 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. Giacomo Indiveri
2. Shih-Chii Liu
3. J. Urgen Schmidhuber
4. David R Ha
5. Yoshua Bengio
6. Sergey Levine
7. Quoc V. Le
8. Chelsea Finn

Citations in the corpus

• Deep learning in neural networks: An overview (2014, methodology): “The Neocognitron (Section 5.4) inspired the Cresceptron (Weng et al., 1992), which adapts its topology during training (Section 5.6.3); compare the incrementally growing and shrinking GMDH networks (1965, Section 5.3).”
• Memory and Information Processing in Neuromorphic Systems (2015, background): “They include convolutional networks which are being explored intensively within the neuromorphic community for visual processing tasks [46].”
• My First Deep Learning System of 1991 + Deep Learning Timeline 1962-2013 (2013, methodology): “Fukushima’s deep Neocognitron architecture [29, 30, 31] incorporated neurophysiological insights (TL 1.1) [49].”