Title :
A self-organization model of feature columns and face responsive neurons in the temporal cortex
Author :
Takahashi, Takashi ; Kurita, Takio
Abstract :
We investigate a self-organizing network model to account for the computational property of the inferotemporal cortex. The network can learn sparse codes for given data with organizing their topographic mapping. Simulation experiments are performed using real face images composed of different individuals at different viewing directions, and the results show that the network evolves the information representation which is consistent with some physiological findings. By analyzing the characteristics of the neuron activities, it is also demonstrated that the present model self-organizes the efficient representation for coding both of the global structure and the finer information of the face images
Keywords :
face recognition; learning (artificial intelligence); neurophysiology; physiological models; self-organising feature maps; computational property; face responsive neurons; feature columns; finer information; global structure; inferotemporal cortex; neuron activities; physiological findings; real face images; self-organizing network model; sparse codes; temporal cortex; topographic mapping; Brain modeling; Computational modeling; Computer networks; Image analysis; Image coding; Information analysis; Information representation; Neurons; Organizing; Self-organizing networks;
Conference_Titel :
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-7044-9
DOI :
10.1109/IJCNN.2001.938996
