Kunihiko Fukushima
Kunihiko Fukushima 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.
Notable scientific achievements
In 1980, Fukushima published the neocognitron,the original deep convolutional neural network architecture. 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. Today, however, the CNN architecture is usually trained through backpropagation. This approach is now heavily used in computer vision.
In 1969 Fukushima introduced the ReLU activation function in the context of visual feature extraction in hierarchical neural networks, which he called "analog threshold element". it is the most popular activation function for deep neural networks.
Education and career
In 1958, Fukushima received his Bachelor of Engineering in electronics from Kyoto University. He became a senior research scientist at the NHK Science & Technology Research Laboratories. In 1989, he joined the faculty of Osaka University. 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.Fukushima acted as founding president of the Japanese Neural Network Society. He also was a founding member on the board of governors of the International Neural Network Society, and president of the Asia-Pacific Neural Network Assembly.
He was one of the board of governors of the International Neural Network Society in 1989-1990 and 1993-2005.