Kunihiko Fukushima (Japanese: 福島 邦彦, born 16 March 1936) 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 Fukuoka, Japan.[1]
Kunihiko Fukushima | |
|---|---|
| Born | 16 March 1936 Japan |
| Citizenship | Japan |
| Alma mater | Kyoto University |
| Known for | Artificial neural networks, Neocognitron, Convolutional neural network architecture, Unsupervised learning, Deep learning, ReLU activation function |
| Awards | IEICE Achievement Award and Excellent Paper Awards, IEEE Neural Networks Pioneer Award, APNNA Outstanding Achievement Award, JNNS Excellent Paper Award, INNS Helmholtz Award, Bower Award and Prize for Achievement in Science |
| Scientific career | |
| Fields | Computer science |
| Institutions | Fuzzy Logic Systems Institute |
Notable scientific achievements
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 1969 Fukushima introduced the ReLU (Rectifier Linear Unit) activation function in the context of visual feature extraction in hierarchical neural networks.[8][9][10] It was later argued that it has strong biological motivations and mathematical justifications.[11][12] In 2011 it was found to enable better training of deeper networks,[13] compared to the widely used activation functions prior to 2011, e.g., the logistic sigmoid (which is inspired by probability theory; see logistic regression) and its more practical[14] counterpart, the hyperbolic tangent. The rectifier is, as of 2017[update], the most popular activation function for deep neural networks.[15]
Education and career
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 of 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]He was one of the board of governors of the International Neural Network Society (INNIS) in 2003.
Awards
In 2020 Fukushima received the Bower Award and Prize for Achievement in Science.[16] He also 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]