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Kunihiko Fukushima

Kunihiko Fukushima (born in Japan) is a Japanese computer scientist, most noted for his work on artificial neural networks and deep learning. He is currently working part-time as a Senior Research Scientist at the Fuzzy Logic Systems Institute in Tokyo.[1]

Kunihiko Fukushima
Alma materKyoto University
Known forArtificial neural networks, Neocognitron, Convolutional neural network architecture, Unsupervised learning, Deep learning
AwardsIEICE Achievement Award and Excellent Paper Awards, IEEE Neural Networks Pioneer Award, APNNA Outstanding Achievement Award, JNNS Excellent Paper Award, INNS Helmholtz Award
Scientific career
FieldsComputer science
InstitutionsFuzzy Logic Systems Institute

In 1980, Fukushima published the neocognitron,[2][3] the original deep convolutional neural network (CNN) architecture.[4][5] Fukushima proposed several supervised and unsupervised learning algorithms to train the parameters of a deep neocognitron such that it could learn internal representations of incoming data.[3][6] Today, however, the CNN architecture is usually trained through backpropagation. This approach is now heavily used in computer vision.[5][7]

In 1958, Fukushima received his Bachelor of Engineering in electronics from Kyoto University.[1] He became a Senior Research Scientist at the NHK Science & Technology Research Laboratories. In 1989, he joined the faculty of Osaka University.[1] In 1999, he joined the faculty of the University of Electro-Communications. In 2001, he joined the faculty of Tokyo University of Technology. From 2006 to 2010, he was a visiting professor at Kansai University.[1]

Fukushima acted as founding President the Japanese Neural Network Society (JNNS). He also was a founding member on the Board of Governors of the International neural network society (INNS), and President of the Asia-Pacific Neural Network Assembly (APNNA).[1]


Fukushima received the IEICE Achievement Award and Excellent Paper Awards, the IEEE Neural Networks Pioneer Award, the APNNA Outstanding Achievement Award, the JNNS Excellent Paper Award and the INNS Helmholtz Award.[1]


  1. ^ a b c d e f CIS Oral History Project (Don Wunsch) (2015). "Interview with Kunihiko Fukushima". IEEE TV. Retrieved 2019-02-27.
  2. ^ Fukushima, Neocognitron (1980). "A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position". Biological Cybernetics. 36 (4): 193–202. doi:10.1007/bf00344251.
  3. ^ a b Fukushima, K. (2007). "Neocognitron". Scholarpedia. 2 (1): 1717. doi:10.4249/scholarpedia.1717.
  4. ^ Fogg, Andrew (2017). "A History of Deep Learning". Retrieved 2019-02-27.
  5. ^ a b Schmidhuber, Jürgen (2015). "Deep Learning". Scholarpedia. 10 (11): 1527–54. CiteSeerX doi:10.1162/neco.2006.18.7.1527. PMID 16764513.
  6. ^ Fukushima, Kunihiko (2018). "Video: Artificial Vision by Deep CNN Neocognitron". Youtube. Retrieved 2019-03-25.
  7. ^ LeCun, Yann; Bengio, Yoshua; Hinton, Geoffrey (2015). "Deep learning". Nature. 521 (7553): 436–444. doi:10.1038/nature14539. PMID 26017442.