摘要
The "Binding Problem" is an important problem across many disciplines, including psychology, neuroscience, computational modeling, and even philosophy. In this work, we proposed a novel computational model, Bayesian Linking Field Model, for feature binding in visual perception, by combining the idea of noisy neuron model, Bayesian method, Linking Field Network and competitive mechanism. Simulation Experiments demonstrated that our model perfectly fulfilled the task of feature binding in visual perception and provided us some enlightening idea for future research.
The 'Binding Problem' is an important problem across many disciplines, including psychology, neuroscience, computational modeling, and even philosophy. In this work, we proposed a novel computational model, Bayesian Linking Field Model, for feature binding in visual perception, by combining the idea of noisy neuron model, Bayesian method, Linking Field Network and competitive mechanism. Simulation Experiments demonstrated that our model perfectly fulfilled the task of feature binding in visual perception and provided us some enlightening idea for future research.
作者
SHI ZhiWei1,2, SHI ZhongZhi1, LIU Xi1,2 & SHI ZhiPing1 1 Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China
2 Graduate University of Chinese Academy of Sciences, Beijing 100049, China
基金
the National Natural Science Foundation of China (Grant No. 60435010)
National High-Tech Program (863 Program) of China (Grant No.2006AA01Z128)
National Basic Research Priorities Program of China (Grant No. 2007CB311004)
