Learning-based system for real-time imaging

Tadashi Ae; Keiichi Sakai; Hiroyuki Araki; Naoya Honda

doi:10.1117/12.341115

9 March 1999 Learning-based system for real-time imaging

Tadashi Ae, Keiichi Sakai, Hiroyuki Araki, Naoya Honda

Proceedings Volume 3647, Applications of Artificial Neural Networks in Image Processing IV; (1999) https://doi.org/10.1117/12.341115
Event: Electronic Imaging '99, 1999, San Jose, CA, United States

Abstract

We are now developing a brain computer with algorithm acquisition function, where a two-level structure is introduced to connect pattern with (meta-)symbol, because we know how to realize algorithm acquisition on symbols. At Level 1 we use a conventional learning method on neural networks, but, at Level 2, we develop a new learning algorithm AST, where an automation-like algorithm with a neural network learning is introduced. This is powerful enough to realize an automatic algorithm acquisition. We will state a two-level structure and the AST learning algorithm. We focus on real-time image understanding which is a realization of human brain with eyes. We will summarize the features of our developing artificial brain system as follows: 1) System for meta-symbol as well as pattern, 2) Architecture artificial memory model to satisfy the features of 1)-3), We introduce a two-level architecture, where the meta-symbol is introduced at Level 2 while the pattern is used for Level 1 as usual.

Citation Download Citation

Tadashi Ae, Keiichi Sakai, Hiroyuki Araki, and Naoya Honda "Learning-based system for real-time imaging", Proc. SPIE 3647, Applications of Artificial Neural Networks in Image Processing IV, (9 March 1999); https://doi.org/10.1117/12.341115

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