Title :
Some learning models of visual system based on local sensory signals integration learning
Author :
Shibata, Katsunari ; Okabe, Yoichi
Author_Institution :
Res. Center for Adv. Sci. & Technol., Tokyo Univ., Japan
Abstract :
The visual system has many interesting abilities like vestibule-ocular reflex. These abilities are helpful for us to perceive the environment effectively and often have adaptability to the environment. LSSI (Local Sensory Signals Integration) learning based on the smoothness of the relation between the spatial and temporal information, has been already proposed. In this paper, some computational learning models, each of which is extension of the LSSI learning, are proposed. Some of the abilities of our visual system, those of head invariant perception, vestibule-ocular reflex and smooth pursuit eye movements, are explained by those models. Basic functions are realized in some simulations using those models
Keywords :
learning (artificial intelligence); neural nets; neurophysiology; physiological models; visual perception; computational learning models; head invariant perception; learning models; local sensory signals integration learning; smooth pursuit eye movements; smoothness; spatial information; temporal information; vestibule-ocular reflex; visual system; Computational modeling; Data mining; Intelligent networks; Neural networks; Neurons; Retina; Smoothing methods; Supervised learning; Visual system;
Conference_Titel :
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-2768-3
DOI :
10.1109/ICNN.1995.488976