The author previously proposed a neural network model neocognitron for robust visual
pattern recognition. This paper proposes an improved version of the neocognitron and …

The exquisite capabilities of biological neural systems for recognizing target patterns subject
to large variations have motivated us to investigate neurophysiologically-inspired …

This chapter introduces the general concepts concerning our face recognition task of
automatic recognition of human faces in dynamic environments. By concentrating on face …

It is well known that the task of automatic face recognition in dynamic environments is very
hard. The key problem is that everyday influences, such as lighting, head pose and …

Do you know about the dark secrets in big evolution concerning the origin of the universe?
Do you know that the Bible sets God's signature on his creation in the beginning? Not all …

Previous work on Fuskushima's neocognitron neural network model has mostly focused on
binary character recognition, but grayscale images are preferable to binary images in real …

Feature extraction transforms an object's image representation to an alternate reduced
representation. Feature selection can be time-consuming and difficult to optimize so we …

A self-organising neural network architecture for grey-scale visual object rcognition is
presented. The network is composed of three processing layers with an architecture …

In the mammalian visual system, magnocellular pathway and parvocellular pathway
cooperatively process visual information in parallel. The magnocellular pathway is more …

Vision research has long been an interesting area to biologists, neural network researchers,
and design engineers. However, even with currently available technology, it is difficult to find …