Kunihiko Fukushima

Kunihiko Fukushima (Japanese: 福島 邦彦) 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]

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 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]